Patent Publication Number: US-2007116300-A1

Title: Channel decoding for wireless telephones with multiple microphones and multiple description transmission

Description:
CROSS REFERENCE TO RELATED APPLICATIONS  
      This application is a continuation-in-part of U.S. patent application Ser. No. 11/215,304 to Chen et al., entitled “Wireless Telephone with Multiple Microphones and Multiple Description Transmission” and filed Aug. 31, 2005, which is a continuation-in-part of U.S. patent application Ser. No. 11/135,491 to Chen, entitled “Wireless Telephone with Adaptive Microphone Array” and filed May 24, 2005, which is a continuation-in-part of U.S. patent application Ser. No. 11/065,131 to Chen, entitled “Wireless Telephone With Uni-Directional and Omni-Directional Microphones” and filed Feb. 24, 2005, which is a continuation-in-part of U.S. patent application Ser. No. 11/018,921 to Chen et al., entitled “Wireless Telephone Having Multiple Microphones” and filed Dec. 22, 2004. The entirety of each of these applications is hereby incorporated by reference as if fully set forth herein. 
    
    
     BACKGROUND  
      1. Field  
      The present invention relates generally to wireless telecommunication devices, and in particular to wireless telephones.  
      2. Background  
      Background noise is an inherent problem in wireless telephone communication. Conventional wireless telephones include a single microphone that receives a near-end user&#39;s voice and outputs a corresponding audio signal for subsequent encoding and transmission to the telephone of a far-end user. However, the audio signal output by this microphone typically includes both a voice component and a background noise component. As a result, the far-end user often has difficulty deciphering the desired voice component against the din of the embedded background noise component.  
      Conventional wireless telephones often include a noise suppressor to reduce the detrimental effects of background noise. A noise suppressor attempts to reduce the level of the background noise by processing the audio signal output by the microphone through various algorithms. These algorithms attempt to differentiate between a voice component of the audio signal and a background noise component of the audio signal, and then attenuate the level of the background noise component.  
      Conventional wireless telephones often also include a voice activity detector (VAD) that attempts to identify and transmit only those portions of the audio signal that include a voice component. One benefit of VAD is that bandwidth is conserved on the telecommunication network because only selected portions of the audio signal are transmitted.  
      In order to operate effectively, both the noise suppressor and the VAD must be able to differentiate between the voice component and the background noise component of the input audio signal. However, in practice, differentiating the voice component from the background noise component is difficult.  
      In addition to background noise, transmission channel impairments can degrade the quality of an audio signal. For example, the audio signal encoded and transmitted by the near-end user&#39;s wireless telephone may be corrupted by transmission channel impairments, and this may cause quality degradation of the audio signal received and decoded by the far-end user&#39;s wireless telephone. In this example, the near-end user&#39;s wireless telephone cannot, by itself, remedy all the adverse effects of transmission channel impairments.  
      What is needed then, is a wireless telephone that better mitigates the effect of background noise present in an input audio signal as compared to conventional wireless telephones, and a transmission system that provides redundancy to combat transmission channel impairments.  
     BRIEF SUMMARY  
      The present invention is directed to a multiple-description transmission system that provides redundancy. The redundancy in this system can be used to improve channel decoding, and therefore combat transmission channel impairments including, but not limited to, bit errors and frame erasures.  
      In a first embodiment of the present invention, there is provided a wireless telephone including a receiver module, a channel decoder, a speech decoder, and a speaker. The receiver module receives a plurality of versions of a voice signal, wherein each version of the voice signal includes a plurality of speech frames. The channel decoder is configured to decode a speech parameter associated with a speech frame from one of the plurality of versions of the voice signal, wherein decoding the speech parameter includes selecting an optimal bit sequence from a plurality of candidate bit sequences and wherein the selection of the optimal bit sequence is based in part on a corresponding speech frame from another version of the plurality of versions of the voice signal. Due to redundancy inherent in the multiple-description transmission, information from the corresponding speech frame can be used to improve the selection of the optimal bit sequence. The speech decoder decodes at least one of the plurality of versions of the voice signal based on the speech parameter to generate an output signal. The speaker receives the output signal and produces a sound pressure wave corresponding thereto.  
      In a second embodiment of the present invention, the channel decoder selects the optimal bit sequence based (i) in part on the corresponding speech frame and (ii) in part on a previous speech frame from at least one of the plurality of versions of the voice signal. Due to the manner in which the speech signal is generated naturally by a human being, some speech parameters—including, but not limited to, pitch period, gain, and spectral envelop shape—vary slowly compared with the frame size and thus have an inherent redundancy. The channel decoder can use the redundancy in these speech parameters to make a better selection of the optimal bit sequence.  
      Further embodiments and features of the present invention, as well as the structure and operation of the various embodiments of the present invention, are described in detail below with reference to the accompanying drawings. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS/FIGURES  
      The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate the present invention and, together with the description, further serve to explain the principles of the invention and to enable a person skilled in the pertinent art to make and use the invention.  
       FIG. 1A  is a functional block diagram of the transmit path of a conventional wireless telephone.  
       FIG. 1B  is a functional block diagram of the receive path of a conventional wireless telephone.  
       FIG. 2  is a schematic representation of the front portion of a wireless telephone in accordance with an embodiment of the present invention.  
       FIG. 3  is a schematic representation of the back portion of a wireless telephone in accordance with an embodiment of the present invention.  
       FIG. 4  is a functional block diagram of a transmit path of a wireless telephone in accordance with an embodiment of the present invention.  
       FIG. 5  illustrates a flowchart of a method for processing audio signals in a wireless telephone having a first microphone and a second microphone in accordance with an embodiment of the present invention.  
       FIG. 6  is a functional block diagram of a signal processor in accordance with an embodiment of the present invention.  
       FIG. 7  illustrates a flowchart of a method for processing audio signals in a wireless telephone having a first microphone and a second microphone in accordance with an embodiment of the present invention.  
       FIG. 8  illustrates voice and noise components output from first and second microphones, in an embodiment of the present invention.  
       FIG. 9  is a functional block diagram of a background noise cancellation module in accordance with an embodiment of the present invention.  
       FIG. 10  is a functional block diagram of a signal processor in accordance with an embodiment of the present invention.  
       FIG. 11  illustrates a flowchart of a method for processing audio signals in a wireless telephone having a first microphone and a second microphone in accordance with an embodiment of the present invention.  
       FIG. 12A  illustrates an exemplary frequency spectrum of a voice component and a background noise component of a first audio signal output by a first microphone, in an embodiment of the present invention.  
       FIG. 12B  illustrates an exemplary frequency spectrum of an audio signal upon which noise suppression has been performed, in accordance with an embodiment of the present invention.  
       FIG. 13  is a functional block diagram of a transmit path of a wireless telephone in accordance with an embodiment of the present invention.  
       FIG. 14  is a flowchart depicting a method for processing audio signals in a wireless telephone having a first microphone and a second microphone in accordance with an embodiment of the present invention.  
       FIG. 15  shows exemplary plots depicting a voice component and a background noise component output by first and second microphones of a wireless telephone, in accordance with an embodiment of the present invention.  
       FIG. 16  shows an exemplary polar pattern of an omni-directional microphone.  
       FIG. 17  shows an exemplary polar pattern of a subcardioid microphone.  
       FIG. 18  shows an exemplary polar pattern of a cardioid microphone.  
       FIG. 19  shows an exemplary polar pattern of a hypercardioid microphone.  
       FIG. 20  shows an exemplary polar pattern of a line microphone.  
       FIG. 21  shows an exemplary microphone array, in accordance with an embodiment of the present invention.  
      FIGS.  22 A-D show exemplary polar patterns of a microphone array.  
       FIG. 22E  shows exemplary directivity patterns of a far-field and a near-field response.  
       FIG. 23  shows exemplary steered and unsteered directivity patterns.  
       FIG. 24  is a functional block diagram of a transmit path of a wireless telephone in accordance with an embodiment of the present invention.  
       FIG. 25  illustrates a multiple description transmission system in accordance with an embodiment of the present invention.  
       FIG. 26  is a functional block diagram of a transmit path of a wireless telephone that can be used in a multiple description transmission system in accordance with an embodiment of the present invention.  
       FIG. 27  illustrates multiple versions of a voice signal transmitted by a first wireless telephone in accordance with an embodiment of the present invention.  
       FIG. 28A ,  FIG. 28B , and  FIG. 28C  depict example trellis diagrams illustrating candidate bit sequences that may be selected by a Viterbi algorithm.  
       FIG. 29  is a functional block diagram of an example receive path in accordance with an embodiment of the present invention.  
       FIG. 30  is a block diagram illustrating a plurality of versions of a voice signal, wherein each version includes a plurality of speech frames.  
       FIG. 31  is a flowchart depicting a method for improving channel decoding in accordance with an embodiment of the present invention. 
    
    
      The present invention will now be described with reference to the accompanying drawings. In the drawings, like reference numbers may indicate identical or functionally similar elements. Additionally, the left-most digit(s) of a reference number may identify the drawing in which the reference number first appears.  
     DETAILED DESCRIPTION  
      The present invention is directed to a multiple-description transmission system that provides redundancy. The redundancy in this system can be used to improve channel decoding, and therefore combat transmission channel impairments—such as, but not limited to, bit errors and frame erasures.  
      The detailed description of the invention is divided into eleven subsections. In subsection I, an overview of the workings of a conventional wireless telephone is given. This discussion facilitates the description of embodiments of the present invention. In subsection II, an overview of a wireless telephone implemented with a first microphone and second microphone is presented. In subsection III, an embodiment is described in which the output of the second microphone is used to cancel a background noise component output by the first microphone. In subsection IV, another embodiment is described in which the output of the second microphone is used to suppress a background noise component output by the first microphone. In subsection V, a further embodiment is discussed in which the output of the second microphone is used to improve VAD technology incorporated in the wireless telephone. In subsection VI, alternative arrangements of the present invention are discussed. In subsection VII, example unidirectional microphones are discussed. In subsection VIII, example microphone arrays are discussed. In subsection IX, a wireless telephone implemented with at least one microphone array is described. In subsection X, a multiple description transmission system in accordance with embodiments of the present invention is described. In subsection XI, improved channel decoding is described.  
     I. Overview of Signal Processing within Conventional Wireless Telephones  
      Conventional wireless telephones use what is commonly referred to as encoder/decoder technology. The transmit path of a wireless telephone encodes an audio signal picked up by a microphone onboard the wireless telephone. The encoded audio signal is then transmitted to another telephone. The receive path of a wireless telephone receives signals transmitted from other wireless telephones. The received signals are then decoded into a format that an end user can understand.  
       FIG. 1A  is a functional block diagram of a typical transmit path  100  of a conventional digital wireless telephone. Transmit path  100  includes a microphone  109 , an analog-to-digital (A/D) converter  101 , a noise suppressor  102 , a voice activity detector (VAD)  103 , a speech encoder  104 , a channel encoder  105 , a modulator  106 , a radio frequency (RF) module  107 , and an antenna  108 .  
      Microphone  109  receives a near-end user&#39;s voice and outputs a corresponding audio signal, which typically includes both a voice component and a background noise component. The A/D converter  101  converts the audio signal from an analog to a digital form. The audio signal is next processed through noise suppressor  102 . Noise suppressor  102  uses various algorithms, known to persons skilled in the pertinent art, to suppress the level of embedded background noise that is present in the audio signal.  
      Speech encoder  104  converts the output of noise suppressor  102  into a channel index. The particular format that speech encoder  104  uses to encode the signal is dependent upon the type of technology being used. For example, the signal may be encoded in formats that comply with GSM (Global Standard for Mobile Communication), CDMA (Code Division Multiple Access), or other technologies commonly used for telecommunication. These different encoding formats are known to persons skilled in the relevant art and for the sake of brevity are not discussed in further detail.  
      As shown in  FIG. 1A , VAD  103  also receives the output of noise suppressor  102 . VAD  103  uses algorithms known to persons skilled in the pertinent art to analyze the audio signal output by noise suppressor  102  and determine when the user is speaking. VAD  103  typically operates on a frame-by-frame basis to generate a signal that indicates whether or not a frame includes voice content. This signal is provided to speech encoder  104 , which uses the signal to determine how best to process the frame. For example, if VAD  103  indicates that a frame does not include voice content, speech encoder  103  may skip the encoding of the frame entirely.  
      Channel encoder  105  is employed to reduce bit errors that can occur after the signal is processed through the speech encoder  104 . That is, channel encoder  105  makes the signal more robust by adding redundant bits to the signal. For example, in a wireless phone implementing the original GSM technology, a typical bit rate at the output of the speech encoder might be about 13 kilobits (kb) per second, whereas, a typical bit rate at the output of the channel encoder might be about 22 kb/sec. The extra bits that are present in the signal after channel encoding do not carry information about the speech; they just make the signal more robust, which helps reduce the bit errors.  
      The modulator  106  combines the digital signals from the channel encoder into symbols, which become an analog wave form. Finally, RF module  107  translates the analog wave forms into radio frequencies, and then transmits the RF signal via antenna  108  to another telephone.  
       FIG. 1B  is a functional block diagram of a typical receive path  120  of a conventional wireless telephone. Receive path  120  processes an incoming signal in almost exactly the reverse fashion as compared to transmit path  100 . As shown in  FIG. 1B , receive path  120  includes an antenna  128 , an RF module  127 , a channel decoder  125 , a speech decoder  124 , a digital to analog (D/A) converter  122 , and a speaker  129 .  
      During operation, an analog input signal is received by antenna  128  and RF module  127  translates the radio frequencies into baseband frequencies. Demodulator  126  converts the analog waveforms back into a digital signal. Channel decoder  125  decodes the digital signal back into the channel index, which speech decoder  124  converts back into digitized speech. D/A converter  122  converts the digitized speech into analog speech. Lastly, speaker  129  converts the analog speech signal into a sound pressure wave so that it can be heard by an end user.  
     II. Overview of a Wireless Telephone Having Two Microphones in Accordance with The Present Invention  
      A wireless telephone in accordance with an embodiment of the present invention includes a first microphone and a second microphone. As mentioned above and as will be described in more detail herein, an audio signal output by the second microphone can be used to improve the quality of an audio signal output by the first microphone or to support improved VAD technology.  
       FIGS. 2 and 3  illustrate front and back portions, respectively, of a wireless telephone  200  in accordance with an embodiment of the present invention. As shown in  FIG. 2 , the front portion of wireless telephone  200  includes a first microphone  201  and a speaker  203  located thereon. First microphone  201  is located so as to be close to a user&#39;s mouth during regular use of wireless telephone  200 . Speaker  203  is located so as to be close to a user&#39;s ear during regular use of wireless telephone  200 .  
      As shown in  FIG. 3 , second microphone  202  is located on the back portion of wireless telephone  200 . Second microphone  202  is located so as to be further away from a user&#39;s mouth during regular use than first microphone  201 , and preferably is located to be as far away from the user&#39;s mouth during regular use as possible.  
      By mounting first microphone  201  so that it is closer to a user&#39;s mouth than second microphone  202  during regular use, the amplitude of the user&#39;s voice as picked up by the first microphone  201  will likely be greater than the amplitude of the user&#39;s voice as picked up by second microphone  202 . Similarly, by so mounting first microphone  201  and second microphone  202 , the amplitude of any background noise picked up by second microphone  202  will likely be greater than the amplitude of the background noise picked up by first microphone  201 . The manner in which the signals generated by first microphone  201  and second microphone  202  are utilized by wireless telephone  200  will be described in more detail below.  
       FIGS. 2 and 3  show an embodiment in which first and second microphones  201  and  202  are mounted on the front and back portion of a wireless telephone, respectively. However, the invention is not limited to this embodiment and the first and second microphones may be located in other locations on a wireless telephone and still be within the scope of the present invention. For performance reasons, however, it is preferable that the first and second microphone be mounted so that the first microphone is closer to the mouth of a user than the second microphone during regular use of the wireless telephone.  
       FIG. 4  is a functional block diagram of a transmit path  400  of a wireless telephone that is implemented with a first microphone and a second microphone in accordance with an embodiment of the present invention. Transmit path  400  includes a first microphone  201  and a second microphone  202 , and a first A/D converter  410  and a second A/D converter  412 . In addition, transmit path  400  includes a signal processor  420 , a speech encoder  404 , a channel encoder  405 , a modulator  406 , an RF module  407 , and an antenna  408 . Speech encoder  404 , channel encoder  405 , modulator  406 , RF module  407 , and antenna  408  are respectively analogous to speech encoder  104 , channel encoder  105 , modulator  106 , RF module  107 , and antenna  108  discussed with reference to transmit path  100  of  FIG. 1A  and thus their operation will not be discussed in detail below.  
      The method by which audio signals are processed along transmit path  400  of the wireless telephone depicted in  FIG. 4  will now be described with reference to the flowchart  500  of  FIG. 5 . The present invention, however, is not limited to the description provided by the flowchart  500 . Rather, it will be apparent to persons skilled in the relevant art(s) from the teachings provided herein that other functional flows are within the scope and spirit of the present invention.  
      The method of flowchart  500  begins at step  510 , in which first microphone  201  outputs a first audio signal, which includes a voice component and a background noise component. A/D converter  410  receives the first audio signal and converts it from an analog to digital format before providing it to signal processor  420 .  
      At step  520 , second microphone  202  outputs a second audio signal, which also includes a voice component and a background noise component. A/D converter  412  receives the second audio signal and converts it from an analog to digital format before providing it to signal processor  420 .  
      At step  530 , signal processor  420  receives and processes the first and second audio signals, thereby generating a third audio signal. In particular, signal processor  420  increases a ratio of the voice component to the noise component of the first audio signal based on the content of the second audio signal to produce a third audio signal.  
      The third audio signal is then provided directly to speech encoder  404 . Speech encoder  404  and channel encoder  405  operate to encode the third audio signal using any of a variety of well known speech and channel encoding techniques. Modulator  406 , RF module and antenna  408  then operate in a well-known manner to transmit the encoded audio signal to another telephone.  
      As will be discussed in more detail herein, signal processor  420  may comprise a background noise cancellation module and/or a noise suppressor. The manner in which the background noise cancellation module and the noise suppressor operate are described in more detail in subsections III and IV, respectively.  
     III. Use of Two Microphones to Perform Background Noise Cancellation in Accordance with an Embodiment of the Present Invention  
       FIG. 6  depicts an embodiment in which signal processor  420  includes a background noise cancellation module  605  and a downsampler  615  (optional). Background noise cancellation module  605  receives the first and second audio signals output by the first and second microphones  201  and  202 , respectively. Background noise cancellation module  605  uses the content of the second audio signal to cancel a background noise component present in the first audio signal to produce a third audio signal. The details of the cancellation are described below with reference to  FIGS. 7 and 8 . The third audio signal is sent to the rest of transmit path  400  before being transmitted to the telephone of a far-end user.  
       FIG. 7  illustrates a flowchart  700  of a method for processing audio signals using a wireless telephone having two microphones in accordance with an embodiment of the present invention. Flowchart  700  is used to facilitate the description of how background noise cancellation module  605  cancels at least a portion of a background noise component included in the first audio signal output by first microphone  201 .  
      The method of flowchart  700  starts at step  710 , in which first microphone  201  outputs a first audio signal. The first audio signal includes a voice component and a background noise component. In step  720 , second microphone  202  outputs a second audio signal. Similar to the first audio signal, the second audio signal includes a voice component and a background noise component.  
       FIG. 8  shows exemplary outputs from first and second microphones  201  and  202 , respectively, upon which background noise cancellation module  605  may operate.  FIG. 8  shows an exemplary first audio signal  800  output by first microphone  201 . First audio signal  800  consists of a voice component  810  and a background noise component  820 , which are also separately depicted in  FIG. 8  for illustrative purposes.  FIG. 8  further shows an exemplary second audio signal  850  output by second microphone  202 . Second audio signal  850  consists of a voice component  860  and a background noise component  870 , which are also separately depicted in  FIG. 8 . As can be seen from  FIG. 8 , the amplitude of the voice component picked up by first microphone  201  (i.e., voice component  810 ) is advantageously greater than the amplitude of the voice component picked up by second microphone  202  (i.e., voice component  860 ), and vice versa for the background noise components. As was discussed earlier, the relative amplitude of the voice component (background noise component) picked up by first microphone  201  and second microphone  202  is a function of their respective locations on wireless telephone  200 .  
      At step  730  ( FIG. 7 ), background noise cancellation module  605  uses the second audio signal to cancel at least a portion of the background noise component included in the first audio signal output by first microphone  201 . Finally, the third audio signal produced by background noise cancellation module  605  is transmitted to another telephone. That is, after background noise cancellation module  605  cancels out at least a portion of the background noise component of the first audio signal output by first microphone  201  to produce a third audio signal, the third audio signal is then processed through the standard components or processing steps used in conventional encoder/decoder technology, which were described above with reference to  FIG. 1A . The details of these additional signal processing steps are not described further for brevity.  
      In one embodiment, background noise cancellation module  605  includes an adaptive filter and an adder.  FIG. 9  depicts a background noise cancellation module  605  including an adaptive filter  901  and an adder  902 . Adaptive filter  901  receives the second audio signal from second microphone  202  and outputs an audio signal. Adder  902  adds the first audio signal, received from first microphone  201 , to the audio signal output by adaptive filter  901  to produce a third audio signal. By adding the first audio signal to the audio signal output by adaptive filter  901 , the third audio signal produced by adder  902  has at least a portion of the background noise component that was present in the first audio signal cancelled out.  
      In another embodiment of the present invention, signal processor  420  includes a background noise cancellation module  605  and a downsampler  615 . In accordance with this embodiment, A/D converter  410  and A/D converter  412  sample the first and second audio signals output by first and second microphones  201  and  202 , respectively, at a higher sampling rate than is typically used within wireless telephones. For example, the first audio signal output by first microphone  201  and the second audio signal output by second microphones  202  can be sampled at 16 kHz by A/D converters  410  and  412 , respectively; in comparison, the typical signal sampling rate used in a transmit path of most conventional wireless telephones is 8 kHz. After the first and second audio signals are processed through background noise cancellation module  605  to cancel out the background noise component from the first audio signal, downsampler  615  downsamples the third audio signal produced by background cancellation module  605  back to the proper sampling rate (e.g. 8 kHz). The higher sampling rate of this embodiment offers more precise time slicing and more accurate time matching, if added precision and accuracy are required in the background noise cancellation module  605 .  
      As mentioned above and as is described in more detail in the next subsection, additionally or alternatively, the audio signal output by the second microphone is used to improve noise suppression of the audio signal output by the first microphone.  
     IV. Use of Two Microphones to Perform Improved Noise Suppression in Accordance with an Embodiment of the Present Invention  
      As noted above, signal processor  420  may include a noise suppressor.  FIG. 10  shows an embodiment in which signal processor  420  includes a noise suppressor  1007 . In accordance with this embodiment, noise suppressor  1007  receives the first audio signal and the second audio signal output by first and second microphones  201  and  202 , respectively. Noise suppressor  1007  suppresses at least a portion of the background noise component included in the first audio signal based on the content of the first audio signal and the second audio signal. The details of this background noise suppression are described in more detail with reference to  FIG. 11 .  
       FIG. 11  illustrates a flowchart  1100  of a method for processing audio signals using a wireless telephone having a first and a second microphone in accordance with an embodiment of the present invention. This method is used to suppress at least a portion of the background noise component included in the output of the first microphone.  
      The method of flowchart  1100  begins at step  1110 , in which first microphone  201  outputs a first audio signal that includes a voice component and a background noise component. In step  1120 , second microphone  202  outputs a second audio signal that includes a voice component and a background noise component.  
      At step  1130 , noise suppressor  1007  receives the first and second audio signals and suppresses at least a portion of the background noise component of the first audio signal based on the content of the first and second audio signals to produce a third audio signal. The details of this step will now be described in more detail.  
      In one embodiment, noise suppressor  1007  converts the first and second audio signals into the frequency domain before suppressing the background noise component in the first audio signal.  FIGS. 12A and 12B  show exemplary frequency spectra that are used to illustrate the function of noise suppressor  1007 .  
       FIG. 12A  shows two components: a voice spectrum component  1210  and a noise spectrum component  1220 . Voice spectrum  1210  includes pitch harmonic peaks (the equally spaced peaks) and the three formants in the spectral envelope.  
       FIG. 12A  is an exemplary plot used for conceptual illustration purposes only. It is to be appreciated that voice component  1210  and noise component  1220  are mixed and inseparable in audio signals picked up by actual microphones. In reality, a microphone picks up a single mixed voice and noise signal and its spectrum.  
       FIG. 12B  shows an exemplary single mixed voice and noise spectrum before noise suppression (i.e., spectrum  1260 ) and after noise suppression (i.e., spectrum  1270 ). For example, spectrum  1260  is the magnitude of a Fast Fourier Transform (FFT) of the first audio signal output by first microphone  201 .  
      A typical noise suppressor keeps an estimate of the background noise spectrum (e.g., spectrum  1220  in  FIG. 12A ), and then compares the observed single voice and noise spectrum (e.g., spectrum  1260  in  FIG. 12B ) with this estimated background noise spectrum to determine whether each frequency component is predominately voice or predominantly noise. If it is considered predominantly noise, the magnitude of the FFT coefficient at that frequency is attenuated. If it is considered predominantly voice, then the FFT coefficient is kept as is. This can be seen in  FIG. 12B .  
      There are many frequency regions where spectrum  1270  is on top of spectrum  1260 . These frequency regions are considered to contain predominantly voice. On the other hand, regions where spectrum  1260  and spectrum  1270  are at different places are the frequency regions that are considered predominantly noise. By attenuating the frequency regions that are predominantly noise, noise suppressor  1007  produces a third audio signal (e.g., an audio signal corresponding to frequency spectrum  1270 ) with an increased ratio of the voice component to background noise component compared to the first audio signal.  
      The operations described in the last two paragraphs above correspond to a conventional single-microphone noise suppression scheme. According to an embodiment of the present invention, noise suppressor  1007  additionally uses the spectrum of the second audio signal picked up by the second microphone to estimate the background noise spectrum  1220  more accurately than in a single-microphone noise suppression scheme.  
      In a conventional single-microphone noise suppressor, background noise spectrum  1220  is estimated between “talk spurts”, i.e., during the gaps between active speech segments corresponding to uttered syllables. Such a scheme works well only if the background noise is relatively stationary, i.e., when the general shape of noise spectrum  1220  does not change much during each talk spurt. If noise spectrum  1220  changes significantly through the duration of the talk spurt, then the single-microphone noise suppressor will not work well because the noise spectrum estimated during the last “gap” is not reliable. Therefore, in general, and especially for non-stationary background noise, the availability of the spectrum of the second audio signal picked up by the second microphone allows noise suppressor  1007  to get a more accurate, up-to-date estimate of noise spectrum  1220 , and thus achieve better noise suppression performance.  
      Note that the spectrum of the second audio signal should not be used directly as the estimate of the noise spectrum  1220 . There are at least two problems with using the spectrum of the second audio signal directly: first, the second audio signal may still have some voice component in it; and second, the noise component in the second audio signal is generally different from the noise component in the first audio signal.  
      To circumvent the first problem, the voice component can be cancelled out of the second audio signal. For example, in conjunction with a noise cancellation scheme, the noise-cancelled version of the first audio signal, which is a cleaner version of the main voice signal, can pass through an adaptive filter. The signal resulting from the adaptive filter can be added to the second audio signal to cancel out a large portion of the voice component in the second audio signal.  
      To circumvent the second problem, an approximation of the noise component in the first audio signal can be determined, for example, by filtering the voice-cancelled version of the second audio signal with adaptive filter  901 .  
      The example method outlined above, which includes the use of a first and second audio signal, allows noise suppressor  1007  to obtain a more accurate and up-to-date estimate of noise spectrum  1220  during a talk spurt than a conventional noise suppression scheme that only uses one audio signal. An alternative embodiment of the present invention can use the second audio signal picked up by the second microphone to help obtain a more accurate determination of talk spurts versus inter-syllable gaps; and this will, in turn, produce a more reliable estimate of noise spectrum  1220 , and thus improve the noise suppression performance.  
      For the particular example of  FIG. 12B , spectrum  1260  in the noise regions is attenuated by 10 dB resulting in spectrum  1270 . It should be appreciated that an attenuation of 10 dB is shown for illustrative purposes, and not limitation. It will be apparent to persons having ordinary skill in the art that spectrum  1260  could be attenuated by more or less than 10 dB.  
      Lastly, the third audio signal is transmitted to another telephone. The processing and transmission of the third audio signal is achieved in like manner to that which was described above in reference to conventional transmit path  100  ( FIG. 1A ).  
      As mentioned above and as is described in more detail in the next subsection, additionally or alternatively, the audio signal output by the second microphone is used to improve VAD technology incorporated within the wireless telephone.  
     V. Use of Two Microphones to Perform Improved VAD in Accordance with an Embodiment of the Present Invention  
       FIG. 13  is a functional block diagram of a transmit path  1300  of a wireless telephone that is implemented with a first microphone and a second microphone in accordance with an embodiment of the present invention. Transmit path  1300  includes a first microphone  201  and a second microphone  202 . In addition, transmit path  1300  includes an A/D converter  1310 , an A/D converter  1312 , a noise suppressor  1307  (optional), a VAD  1320 , a speech encoder  1304 , a channel encoder  1305 , a modulator  1306 , an RF module  1307 , and an antenna  1308 . Speech encoder  1304 , channel encoder  1305 , modulator  1306 , RF module  1307 , and antenna  1308  are respectively analogous to speech encoder  104 , channel encoder  105 , modulator  106 , RF module  107 , and antenna  108  discussed with reference to transmit path  100  of  FIG. 1A  and thus their operation will not be discussed in detail below.  
      For illustrative purposes and not limitation, transmit path  1300  is described in an embodiment in which noise suppressor  1307  is not present. In this example embodiment, VAD  1320  receives the first audio signal and second audio signal output by first microphone  201  and the second microphone  202 , respectively. VAD  1320  uses both the first audio signal output by the first microphone  201  and the second audio signal output by second microphone  202  to provide detection of voice activity in the first audio signal. VAD  1320  sends an indication signal to speech encoder  1304  indicating which time intervals of the first audio signal include a voice component. The details of the function of VAD  1320  are described with reference to  FIG. 14 .  
       FIG. 14  illustrates a flowchart  1400  of a method for processing audio signals in a wireless telephone having a first and a second microphone, in accordance with an embodiment of the present invention. This method is used to detect time intervals in which an audio signal output by the first microphone includes a voice component.  
      The method of flowchart  1400  begins at step  1410 , in which first microphone  201  outputs a first audio signal the includes a voice component and a background noise component. In step  1420 , second microphone  202  outputs a second audio signal that includes a voice component and a background noise component.  
       FIG. 15  shows exemplary plots of the first and second audio signals output by first and second microphones  201  and  202 , respectively. Plot  1500  is a representation of the first audio signal output by first microphone  201 . The audio signal shown in plot  1500  includes a voice component  1510  and a background noise component  1520 . The audio signal shown in plot  1550  is a representation of the second audio signal output by second microphone  202 . Plot  1550  also includes a voice component  1560  and a background noise component  1570 . As discussed above, since first microphone  201  is preferably closer to a user&#39;s mouth during regular use than second microphone  202 , the amplitude of voice component  1510  is greater than the amplitude of voice component  1560 . Conversely, the amplitude of background noise component  1570  is greater than the amplitude of background noise component  1520 .  
      As shown in step  1430  of flowchart.  1400 , VAD  1320 , based on the content of the first audio signal (plot  1500 ) and the second audio signal (plot  1550 ), detects time intervals in which voice component  1510  is present in the first audio signal. By using the second audio signal in addition to the first audio signal to detect voice activity in the first audio signal, VAD  1320  achieves improved voice activity detection as compared to VAD technology that only monitors one audio signal. That is, the additional information coming from the second audio signal, which includes mostly background noise component  1570 , helps VAD  1320  better differentiate what in the first audio signal constitutes the voice component, thereby helping VAD  1320  achieve improved performance.  
      As an example, according to an embodiment of the present invention, in addition to all the other signal features that a conventional single-microphone VAD normally monitors, VAD  1320  can also monitor the energy ratio or average magnitude ratio between the first audio signal and the second audio signal to help it better detect voice activity in the first audio signal. This possibility is readily evident by comparing first audio signal  1500  and second audio signal  1550  in  FIG. 15 . For audio signals  1500  and  1550  shown in  FIG. 15 , the energy of first audio signal  1500  is greater than the energy of second audio signal  1550  during talk spurt (active speech). On the other hand, during the gaps between talk spurts (i.e. background noise only regions), the opposite is true. Thus, the energy ratio of the first audio signal over the second audio signal goes from a high value during talk spurts to a low value during the gaps between talk spurts. This change of energy ratio provides a valuable clue about voice activity in the first audio signal. This valuable clue is not available if only a single microphone is used to obtain the first audio signal. It is only available through the use of two microphones, and VAD  1320  can use this energy ratio to improve its accuracy of voice activity detection.  
     VI. Alternative Embodiments of the Present Invention  
      In an example alternative embodiment (not shown), signal processor  420  includes both a background noise cancellation module and a noise suppressor. In this embodiment, the background noise cancellation module cancels at least a portion of a background noise component included in the first audio signal based on the content of the second audio signal to produce a third audio signal. Then the noise suppressor receives the second and third audio signals and suppresses at least a portion of a residual background noise component present in the third audio signal based on the content of the second audio signal and the third audio signal, in like manner to that described above. The noise suppressor then provides a fourth audio signal to the remaining components and/or processing steps, as described above.  
      In another alternative example embodiment, a transmit path having a first and second microphone can include a signal processor (similar to signal processor  420 ) and a VAD (similar to VAD  1320 ). A person having ordinary skill in the art will appreciate that a signal processor can precede a VAD in a transmit path, or vice versa. In addition, a signal processor and a VAD can process the outputs of the two microphones contemporaneously. For illustrative purposes, and not limitation, an embodiment in which a signal processor precedes a VAD in a transmit path having two microphones is described in more detail below.  
      In this illustrative embodiment, a signal processor increases a ratio of a voice component to a background noise component of a first audio signal based on the content of at least one of the first audio signal and a second audio signal to produce a third audio signal (similar to the function of signal processor  420  described in detail above). The third audio signal is then received by a VAD. The VAD also receives a second audio signal output by a second microphone (e.g., second microphone  202 ). In a similar manner to that described in detail above, the VAD detects time intervals in which a voice component is present in the third signal based on the content of the second audio signal and the third audio signal.  
      In a still further embodiment, a VAD can precede a noise suppressor, in a transmit path having two microphones. In this embodiment, the VAD receives a first audio signal and a second audio signal output by a first microphone and a second microphone, respectively, to detect time intervals in which a voice component is present in the first audio signal based on the content of the first and second audio signals, in like manner to that described above. The noise suppressor receives the first and second audio signals and suppresses a background noise component in the first audio signal based on the content of the first audio signal and the second audio signal, in like manner to that described above.  
     VII. Embodiments Implementing Uni-Directional Microphones  
      At least one of the microphones used in exemplary wireless telephone  200  can be a unidirectional microphone in accordance with an embodiment of the present invention. As will be described in more detail below, a uni-directional microphone is a microphone that is most sensitive to sound waves originating from a particular direction (e.g., sound waves coming from directly in front of the microphone). Some of the information provided below concerning uni-directional and omni-directional microphones was found on the following website: &lt;http://www.audio-technica.com/using/mphones/guide/pattern.html&gt;.  
      Persons skilled in the relevant art(s) will appreciate that microphones are often identified by their directional properties—that is, how well the microphones pick up sound from various directions. Omni-directional microphones pick up sound from just about every direction equally. Thus, omni-directional microphones work substantially the same pointed away from a subject as pointed toward it, if the distances are equal.  FIG. 16  illustrates a polar pattern  1600  of an omni-directional microphone. A polar pattern is a round plot that illustrates the sensitivity of a microphone in decibels (dB) as it rotates in front of a fixed sound source. Polar patterns, which are also referred to in the art as “pickup patterns” or “directional patterns,” are well-known graphical aids for illustrating the directional properties of a microphone. As shown by polar pattern  1600  of  FIG. 16 , an omni-directional microphone picks up sounds equally in all directions.  
      In contrast to omni-directional microphones, uni-directional microphones are specially designed to respond best to sound originating from a particular direction while tending to reject sound that arrives from other directions. This directional ability is typically implemented through the use of external openings and internal passages in the microphone that allow sound to reach both sides of the diaphragm in a carefully controlled way. Thus, in an example uni-directional microphone, sound arriving from the front of the microphone will aid diaphragm motion, while sound arriving from the side or rear will cancel diaphragm motion.  
      Exemplary types of uni-directional microphones include but are not limited to subcardioid, cardioid, hypercardioid, and line microphones. Polar patterns for example microphones of each of these types are provided in  FIG. 17  (subcardioid),  FIG. 18  (cardioid),  FIG. 19  (hypercardioid) and  FIG. 20  (line). Each of these figures shows the acceptance angle and null(s) for each microphone. The acceptance angle is the maximum angle within which a microphone may be expected to offer uniform sensitivity. Acceptance angles may vary with frequency; however, high-quality microphones have polar patterns which change very little when plotted at different frequencies. A null defines the angle at which a microphone exhibits minimum sensitivity to incoming sounds.  
       FIG. 17  shows an exemplary polar pattern  1700  for a subcardioid microphone. The acceptance angle for polar pattern  1700  spans 170-degrees, measured in a counterclockwise fashion from line  1705  to line  1708 . The null for polar pattern  1700  is not located at a particular point, but spans a range of angles—i.e., from line  1718  to line  1730 . Lines  1718  and  1730  are at 100-degrees from upward-pointing vertical axis  1710 , as measured in a counterclockwise and clockwise fashion, respectively. Hence, the null for polar pattern  1700  spans 160-degrees from line  1718  to line  1730 , measured in a counterclockwise fashion.  
       FIG. 18  shows an exemplary polar pattern  1800  for a cardioid microphone. The acceptance angle for polar pattern  1800  spans 120-degrees, measured in a counterclockwise fashion from line  1805  to line  1808 . Polar pattern  1800  has a single null  1860  located 180-degrees from upward-pointing vertical axis  1810 .  
       FIG. 19  shows an exemplary polar pattern  1900  for a hypercardioid microphone. The acceptance angle for polar pattern  1900  spans 100-degrees, measured in a counterclockwise fashion from line  1905  to line  1908 . Polar pattern  1900  has a first null  1920  and a second null  1930 . First null  1920  and second null  1930  are each 110-degrees from upward-pointing vertical axis  1910 , as measured in a counterclockwise and clockwise fashion, respectively.  
       FIG. 20  shows an exemplary polar pattern  2000  for a line microphone. The acceptance angle for polar pattern  2000  spans 90-degrees, measured in a counterclockwise fashion from line  2005  to line  2008 . Polar pattern  2000  has a first null  2020  and a second null  2030 . First null  2020  and second null  2030  are each 120-degrees from upward-pointing vertical axis  2010 , as measured in a counterclockwise and clockwise fashion, respectively.  
      A uni-directional microphone&#39;s ability to reject much of the sound that arrives from off-axis provides a greater working distance or “distance factor” than an omni-directional microphone. Table 1, below, sets forth the acceptance angle, null, and distance factor (DF) for exemplary microphones of differing types. As Table 1 shows, the DF for an exemplary cardioid microphone is 1.7 while the DF for an exemplary omni-directional microphone is 1.0. This means that if an omni-directional microphone is used in a uniformly noisy environment to pick up a desired sound that is 10 feet away, a cardioid microphone used at 17 feet away from the sound source should provide the same results in terms of the ratio of desired signal to ambient noise. Among the other exemplary microphone types listed in Table 1, the subcardioid microphone performs equally well at 12 feet, the hypercardioid at 20 feet, and the line at 25 feet.  
               TABLE 1                          Properties of Exemplary Microphones of Differing Types                                         Omni-                           direc-           tional   Subcardioid   Cardioid   Hypercardioid   Line                                                 Acceptance   —   170°   120°   100°    90°       Angle       Null   None   100°   180°   110°   120°       Distance   1.0   1.2   1.7   2.0   2.5       Factor (DF)                  
 
     VIII. Microphone Arrays  
      A wireless telephone in accordance with an embodiment of the present invention can include at least one microphone array. As will be described in more detail below, a microphone array includes a plurality of microphones that are coupled to a digital signal processor (DSP). The DSP can be configured to adaptively combined the audio signals output by the microphones in the microphone array to effectively adjust the sensitivity of the microphone array to pick up sound waves originating from a particular direction. Some of the information provided below on microphone arrays was found on the following website: &lt;http://www.idiap.ch/˜mccowan/arrays/tutorial.pdf&gt;.  
      In a similar manner to unidirectional microphones, a microphone array can be used to enhance the pick up of sound originating from a particular direction, while tending to reject sound that arrives from other directions. Like uni-directional microphones, the sensitivity of a microphone array can be represented by a polar pattern or a directivity pattern. However, unlike uni-directional microphones, the direction in which a microphone array is most sensitive is not fixed. Rather, it can be dynamically adjusted. That is, the orientation of the main lobe of a polar pattern or directivity pattern of a microphone array can be dynamically adjusted.  
      A. Background on Microphone Arrays  
       FIG. 21  is a representation of an example microphone array  2100  in accordance with an embodiment of the present invention. Microphone array  2100  includes a plurality of microphones  2101 , a plurality of A/D converters  2103  and a digital signal processor (DSP)  2105 . Microphones  2101  function to convert a sound wave impinging thereon into audio output signals, in like manner to conventional microphones. A/D converters  2103  receive the analog audio output signals from microphones  2101  and convert these signals to digital form in a manner well-known in the relevant art(s). DSP  2105  receives and combines the digital signals from A/D converters  2103  in a manner to be described below.  
      Also included in  FIG. 21  are characteristic dimensions of microphone array  2100 . In an embodiment, microphones  2101  in microphone array  2100  are approximately evenly spaced apart by a distance d. The distance between the first and last microphone in microphone array  2100  is designated as L. The following relationship is satisfied by characteristic dimensions L and d: 
 
 L =( N− 1) d,   Eq. (1) 
 
 where N is the number of microphones in the array. 
 
      Characteristic dimensions d and/or L impact the response of microphone array  2100 . More particularly, the ratio of the total length of microphones  2101  to the wavelength of the impinging sound (i.e., L/λ) affects the response of microphone array  2100 . For example, FIGS.  22 A-D show the polar patterns of a microphone array having different values of L/λ, demonstrating the impact that this ratio has on the microphone array&#39;s response.  
      As can be seen from FIGS.  22 A-D, similar to uni-directional microphones, a microphone array has directional properties. In other words, the response of a microphone array to a particular sound source is dependent on the direction of arrival (DOA) of the sound waves emanating from the sound source in relation to the microphone array. The DOA of a sound wave can be understood by referring to  FIG. 21 . In  FIG. 21 , sound waves emanating from a sound source are approximated (using the far-field approximation described below) by a set of parallel wavefronts  2110  that propagate toward microphone array  2100  in a direction indicated by arrow  2115 . The DOA of parallel wavefronts  2110  can be defined as an angle φ that arrow  2115  makes with the axis along which microphones  2101  lie, as shown in the figure.  
      In addition to the DOA of a sound wave, the response of a microphone array is affected by the distance a sound source is from the array. Sound waves impinging upon a microphone array can be classified according to a distance, r, these sound waves traveled in relation to the characteristic dimension L and the wavelength of the sound λ. In particular, if r is greater than 2L 2 /λ, then the sound source is classified as a far-field source and the curvature of the wavefronts of the sound waves impinging upon the microphone array can be neglected. If r is not greater than 2L 2 /λ, then the sound source is classified as a near-field source and the curvature of the wavefronts can not be neglected.  
       FIG. 22E  shows an exemplary directivity pattern illustrating the response of a microphone array for a near-field source (dotted line) and a far-field source (solid line). In the directivity pattern, the array&#39;s response is plotted on the vertical axis and the angular dependence is plotted on the horizontal axis.  
      In a similar manner to uni-directional microphones, a maximum and a minimum sensitivity angle can be defined for a microphone array. A maximum sensitivity angle of a microphone array is defined as an angle within which a sensitivity of the microphone array is above a predetermined threshold. A minimum sensitivity angle of a microphone array is defined as an angle within which a sensitivity of the microphone array is below a predetermined threshold.  
      B. Examples of Steering a Response of a Microphone Array  
      As mentioned above, DSP  2105  of microphone array  2100  can be configured to combine the audio output signals received from microphones  2101  (in a manner to be described presently) to effectively steer the directivity pattern of microphone array  2100 .  
      In general, DSP  2105  receives N audio signals and produces a single audio output signal, where again N is the number of microphones in the microphone array  2100 . Each of the N audio signals received by DSP  2105  can be multiplied by a weight factor, having a magnitude and phase, to produce N products of audio signals and weight factors. DSP  2105  can then produce a single audio output signal from the collection of received audio signals by summing the N products of audio signals and weight factors.  
      By modifying the weight factors before summing the products, DSP  2105  can alter the directivity pattern of microphone array  2100 . Various techniques, called beamforming techniques, exist for modifying the weight factors in particular ways. For example, by modifying the amplitude of the weight factors before summing, DSP  2105  can modify the shape of a directivity pattern. As another example, by modifying the phase of the weight factors before summing, DSP  2105  can control the angular location of a main lobe of a directivity pattern of microphone array  2100 .  FIG. 23  illustrates an example in which the directivity pattern of a microphone array is steered by modifying the phases of the weight factors before summing. As can be seen from  FIG. 23 , in this example, the main lobe of the directivity pattern is shifted by approximately 45 degrees.  
      As is well-known in the relevant art(s), beamforming techniques can be non-adaptive or adaptive. Non-adaptive beamforming techniques are not dependent on the data. In other words, non-adaptive beamforming techniques apply the same algorithm regardless of the incoming sound waves and resulting audio signals. In contrast, adaptive beamforming techniques are dependent on the data. Accordingly, adaptive beamforming techniques can be used to adaptively determine a DOA of a sound source and effectively steer the main lobe of a directivity pattern of a microphone array in the DOA of the sound source. Example adaptive beamforming techniques include, but are not limited to, Frost&#39;s algorithm, linearly constrained minimum variance algorithms, generalized sidelobe canceller algorithms, or the like.  
      It is to be appreciated that  FIG. 21  is shown for illustrative purposes only, and not limitation. For example, microphones  2101  need not be evenly spaced apart. In addition, microphone array  2100  is shown as a one-dimensional array; however two-dimensional arrays are contemplated within the scope of the present invention. As a person having ordinary skill in the art knows, two-dimensional microphone arrays can be used to determine a DOA of a sound source with respect to two distinct dimensions. In contrast, a one-dimensional array can only detect the DOA with respect to one dimension.  
     IX. Embodiments Implementing Microphone Arrays  
      In embodiments to be described below, microphone  201  and/or microphone  202  of wireless telephone  200  ( FIGS. 2 and 3 ) can be replaced with a microphone array, similar to microphone array  2100  shown in  FIG. 21 .  
       FIG. 24  is an example transmit path  2400  of a wireless telephone implemented with a first microphone array  201 ′ and a second microphone array  202 ′. First microphone array  201 ′ and second microphone array  202 ′ function in like manner to exemplary microphone array  2100  ( FIG. 21 ) described above. In particular, microphones  2401   a - n  and  2411   a - n  function to convert sound waves impinging thereon into audio signals. A/D converters  2402   a - n  and  2412   a - n  function to convert the analog audio signals received from microphones  2401   a - n  and  2411   a - n , respectively, into digital audio signals. DSP  2405  receives the digital audio signals from A/D converters  2402   a - n  and combines them to produce a first audio output signal that is sent to signal processor  420 ′. Similarly, DSP  2415  receives the digital audio signals from A/D converters  2412   a - n  and combines them to produce a second audio output signal that is sent to signal processor  420 ′.  
      The remaining components in transmit path  2400  (namely, signal processor  420 ′, speech encoder  404 ′, channel encoder  405 ′, modulator  406 ′, RF module  407 ′ and antenna  408 ′) function in substantially the same manner as the corresponding components discussed with reference to  FIG. 4 . Accordingly, the functionality of the remaining components is not discussed further.  
      In an embodiment of the present invention, DSP  2405 , using adaptive beamforming techniques, determines a DOA of a voice of a user of a wireless telephone based on the digital audio signals received from A/D converters  2402   a - n . DSP  2405  then adaptively combines the digital audio signals to effectively steer a maximum sensitivity angle of microphone array  201 ′ so that the mouth of the user is within the maximum sensitivity angle. In this way, the single audio signal output by DSP  2405  will tend to include a cleaner version of the user&#39;s voice, as compared to an audio signal output from a single microphone (e.g., microphone  201 ). The audio signal output by DSP  2405  is then received by signal processor  420 ′ and processed in like manner to the audio signal output by microphone  201  ( FIG. 4 ), which is described in detail above.  
      In another embodiment of the present invention, DSP  2415  receives the digital audio signals from A/D converters  2412   a - n  and, using adaptive beamforming techniques, determines a DOA of a voice of a user of the wireless telephone based on the digital audio signals. DSP  2415  then adaptively combines the digital audio signals to effectively steer a minimum sensitivity angle of microphone array  202 ′ so that the mouth of the user is within the minimum sensitivity angle. In this way, the single audio signal output by DSP  2415  will tend to not include the user&#39;s voice; hence the output of DSP  2415  will tend to include a purer version of background noise, as compared to an audio signal output from a single microphone (e.g., microphone  202 ). The audio signal output by DSP  2415  is then received by signal processor  420 ′ and processed in like manner to the audio signal output by microphone  202  ( FIG. 4 ), which is described in detail above.  
      In most situations background noise is non-directional—it is substantially the same in all directions. However, in some situations a single noise source (e.g., a jackhammer or ambulance) accounts for a majority of the background noise. In these situations, the background noise is highly directional. In an embodiment of the invention, DSP  2405  is configured to determine a DOA of a highly directional background noise source. DSP  2405  is further configured to adaptively combine the digital audio signals to effectively steer a minimum sensitivity angle of microphone array  201 ′ so that the highly directional background noise source is within the minimum sensitivity angle. In this way, microphone array  201 ′ will tend to reject sound originating from the DOA of the highly directional background noise source. Hence, microphone array  201 ′ will consequently pick up a purer version of a user&#39;s voice, as compared to a single microphone (e.g., microphone  201 ).  
      In another embodiment, DSP  2415  is configured to determine a DOA of a highly directional background noise source. DSP  2415  is further configured to adaptively combine the digital audio signals from A/D converters  2412   a - n  to effectively steer a maximum sensitivity angle of microphone array  202 ′ so that the highly directional background noise source is within the maximum sensitivity angle. In this way, microphone array  202 ′ will tend to pick-up sound originating from the DOA of the highly directional background noise source. Hence, microphone array  202 ′ will consequently pick up a purer version of the highly directional background noise, as compared to a single microphone (e.g., microphone  202 ).  
      In a further embodiment (not shown), a wireless telephone includes a first and second microphone array and a VAD. In this embodiment, a DSP is configured to determine a DOA of a highly directional background noise and a DOA of a user&#39;s voice. In addition, in a similar fashion to that described above, the VAD detects time intervals in which a voice component is present in the audio signal output by the first microphone array. During time intervals in which a voice signal is present in the audio signal output from the first microphone array, a DSP associated with the second microphone array adaptively steers a minimum sensitivity angle of the second microphone array so that the mouth of the user is within the minimum sensitivity angle. During time intervals in which a voice signal is not present in the audio signal output from the first microphone array, a DSP associated with the second microphone array adaptively steers a maximum sensitivity angle of the second microphone array so that the highly directional background noise source is within the maximum sensitivity angle. In other words, the second microphone array, with the help of the VAD, adaptively switches between the following: (i) rejecting the user&#39;s voice during time intervals in which the user is talking; and (ii) preferentially picking up a highly directional background noise sound during time intervals in which the user is not talking. In this way, the second microphone array can pick up a purer version of background noise as compared to a single microphone.  
      It is to be appreciated that the embodiments described above are meant for illustrative purposes only, and not limitation. In particular, it is to be appreciated that the term “digital signal processor,” “signal processor” or “DSP” used above and below can mean a single DSP, multiple DSPs, a single DSP algorithm, multiple DSP algorithms, or combinations thereof. For example, DSP  2405 , DSP  2415  and/or signal processor  420 ′ ( FIG. 24 ) can represent different DSP algorithms that function within a single DSP. Additionally or alternatively, various combinations of DSP  2405 , DSP  2415  and/or signal processor  420 ′ can be implemented in a single DSP or multiple DSPs as is known by a person skilled in the relevant art(s).  
     X. Multiple Description Transmission System in Accordance with an Embodiment of the Present Invention  
       FIG. 25  illustrates a multiple description transmission system  2500  that provides redundancy to combat transmission channel impairments in accordance with embodiments of the present invention. Multiple description transmission system  2500  includes a first wireless telephone  2510  and a second wireless telephone  2520 . First wireless telephone  2510  transmits multiple versions  2550  of a voice signal to second wireless telephone  2520 .  
       FIG. 26  is a functional block diagram illustrating an example transmit path  2600  of first wireless telephone  2510  and an example receive path  2650  of second wireless telephone  2520 . As shown in  FIG. 26 , first wireless telephone  2510  comprises an array of microphones  2610 , an encoder  2620 , and a transmitter  2630 . Each microphone in microphone array  2610  is configured to receive voice input from a user (in the form of a sound pressure wave) and to produce a voice signal corresponding thereto. Microphone array  2610  can be, for example, substantially the same as microphone array  2100  ( FIG. 21 ). Encoder  2620  is coupled to microphone array  2610  and configured to encode each of the voice signals. Encoder  2620  can include, for example, a speech encoder and channel encoder similar to speech encoder  404  and channel encoder  405 , respectively, which are each described above with reference to  FIG. 4 . Additionally, encoder  2620  may optionally include a DSP, similar to DSP  420  ( FIG. 4 ).  
      Transmitter  2630  is coupled to encoder  2620  and configured to transmit each of the encoded voice signals. For example,  FIG. 25  conceptually illustrates an example multiple description transmission system. In  FIG. 25 , first wireless telephone  2510  transmits a first signal  2550 A and a second signal  2550 B to second wireless telephone  2520 . It is to be appreciated, however, that first wireless telephone  2510  can transmit more than two signals (e.g., three, four, five, etc.) to second wireless telephone  2520 . Transmitter  2630  of first wireless telephone  2510  can include, for example, a modulator, an RF module, and an antenna similar to modulator  406 , RF module  407 , and antenna  408 , respectively, which, as described above with reference to  FIG. 4 , collectively function to transmit encoded voice signals.  
      In alternative embodiments, first wireless telephone  2510  can include multiple encoders and transmitters. For instance, first wireless telephone  2510  can include multiple transmit paths similar to transmit path  100  ( FIG. 1A ), where each transmit path corresponds to a single microphone of microphone array  2610  of first wireless telephone  2510 .  
      As shown in receive path  2650  of  FIG. 26 , second wireless telephone  2520  comprises a receiver module  2660 , a decoder  2670 , and a speaker  2680 . Receiver module  2660  is configured to receive transmitted signals  2550  ( FIG. 25 ). For example, receiver module  2660  can include an antenna, an RF module, and a demodulator similar to antenna  128 , RF module  127 , and demodulator  126 , respectively, which, as described above with reference to  FIG. 1B , collectively function to receive transmitted signals. Decoder  2670  is coupled to receiver module  2660  and configured to decode the signals received by receiver module  2660 , thereby producing an output signal. For example, decoder  2670  can include a channel decoder and speech decoder similar to channel decoder  125  and speech decoder  124 , respectively, which, as described above with reference to  FIG. 1B , collectively function to decode a received signal. Additionally, decoder  2670  may optionally include a DSP. Speaker  2680  receives the output signal from decoder  2670  and produces a pressure sound wave corresponding thereto. For example, speaker  2680  can be similar to speaker  129  ( FIG. 1B ). Additionally, a power amplifier (not shown) can be included before speaker  2680  (or speaker  129 ) to amplify the output signal before it is sent to speaker  2680  (speaker  129 ) as would be apparent to a person skilled in the relevant art(s).  
      In a first embodiment of the present invention, decoder  2670  is further configured to perform two functions: (i) time-align the signals received by receiver module  2660 , and (ii) combine the time-aligned signals to produce the output signal. As is apparent from  FIG. 21 , due to the spatial separation of the microphones in a microphone array, a sound wave emanating from the mouth of a user may impinge upon each microphone in the array at different times. For example, with reference to  FIG. 21 , parallel wave fronts  2110  will impinge upon the left-most microphone of microphone array  2100  before it impinges upon the microphone separated by a distance d from the left-most microphone. Since there can be a time-delay with respect to when the sound waves impinge upon the respective microphones in microphone array  2610 , there will be a corresponding time-delay with respect to the audio signals output by the respective microphones. Decoder  2670  of second wireless telephone  2520  can compensate for this time-delay by time-aligning the audio signals.  
      For example,  FIG. 27  shows a first audio signal S 1  and a second audio signal S 2  corresponding to the output of a first and second microphone, respectively, of first wireless telephone  2510 . Due to the relative location of the microphones on first wireless telephone  2510 , second audio signal S 2  is time-delayed by an amount t 1  compared to first audio signal S 1 . Decoder  2670  of second wireless telephone  2520  can be configured to time-align first audio signal S 1  and second audio signal S 2 , for example, by time-delaying first audio signal S 1  by an amount equal to t 1 .  
      As mentioned above, according to the first embodiment, decoder  2670  of second wireless telephone  2520  is further configured to combine the time-aligned audio signals. Since the respective voice components of first audio signal S 1  and second audio signal S 2  are presumably nearly identical but the respective noise components in each audio signal are not, the voice components will tend to add-up in phase, whereas the noise components, in general, will not. In this way, by combining the audio signals after time-alignment, the combined output signal will have a higher signal-to-noise ratio than either first audio signal S 1  or second audio signal S 2 .  
      In a second embodiment of the present invention, decoder  2670  of second wireless telephone  2520  is configured to perform the following functions. First, decoder  2670  is configured to detect a direction of arrival (DOA) of a sound wave emanating from the mouth of a user of first wireless telephone  2510  based on transmitted signals  2550  received by receiver module  2660  of second wireless telephone  2520 . Decoder  2670  can determine the DOA of the sound wave in a similar manner to that described above with reference to  FIGS. 21 through 24 .  
      Second, decoder  2670 , which as mentioned above may optionally include a DSP, is configured to adaptively combine the received signals based on the DOA to produce the output signal. By adaptively combining the received signals based on the DOA, decoder  2670  of second wireless telephone  2520  can effectively steer a maximum sensitivity angle of microphone array  2610  of first wireless telephone  2510  so that the mouth of the user of first wireless telephone  2510  is within the maximum sensitivity angle. As defined above, the maximum sensitivity angle is an angle within which a sensitivity of microphone array  2610  is above a threshold.  
      In a third embodiment of the present invention, for each voice frame of the signals received by receiver module  2660 , decoder  2670  of second wireless telephone  2520  is configured to perform the following functions. First, decoder  2670  is configured to estimate channel impairments (e.g., bit errors and frame loss). That is, decoder  2670  is configured to determine the degree of channel impairments for each voice frame of the received signals. For example, for a given frame, decoder  2670  can estimate whether the channel impairments exceed a threshold. The estimate can be based on signal-to-noise ratio (S/N) or carrier-to-interference ratio (C/I) of a channel, the bit error rate, block error rate, frame error rate, and or the like. Second, decoder  2670  is configured to decode a received signal with the least channel impairments, thereby producing the output signal for the respective voice frames.  
      By adaptively decoding the signal with the least channel impairments for the respective voice frames, decoder  2670  is configured to decode the best signal for a given time. That is, at different times the multiple versions  2550  of the voice signal transmitted by first wireless telephone  2510  may be subject to different channel impairments. For example, for a given voice frame, first signal  2550 A may have less channel impairments than second signal  2550 B. During this voice frame, decoding first signal  2550 A may lead to a cleaner and better quality voice signal. However, during a subsequent voice frame, first signal  2550 A may have more channel impairments than second signal  2550 B. During this subsequent voice frame, decoding second signal  2550 B may lead to a cleaner and better quality voice signal.  
      In a fourth embodiment of the present invention, for each voice frame of the signals received by receiver module  2660 , decoder  2670  is configured to estimate channel impairments and dynamically discard those received signals having a channel impairment worse than a threshold. Then, decoder  2670  is further configured to combine the non-discarded received signals according to either the first or second embodiment described above. That is, decoder  2670  can be configured to time-align and combine the non-discarded received signals in accordance with the first embodiment. Alternatively, decoder  2670  can be configured to combine the non-discarded received signals to effectively steer microphone array  2610  of first wireless telephone  2510  in accordance with the second embodiment.  
      In a fifth embodiment of the present invention, encoder  2620  of first wireless telephone  2510  is configured to encode the voice signals at different bit rates. For example, encoder  2620  can be configured to encode one of the voice signals at a first bit rate (“a main channel”) and each of the other voice signals at a bit rate different from the first bit rate (“auxiliary channels”). The main channel can be encoded and transmitted, for example, at the same bit rate as a conventional single-channel wireless telephone (e.g., 22 kilobits per second); whereas the auxiliary channels can be encoded and transmitted, for example, at a bit rate lower than a conventional single-channel wireless telephone (e.g., 8 kilobits per second or 4 kilobits per second). In addition, different ones of the auxiliary channels can be encoded and transmitted at different bit rates. For example, a first of the auxiliary channels can be encoded and transmitted at 8 kilobits per second; whereas a second and third auxiliary channel can be encoded and transmitted at 4 kilobits per second. Decoder  2670  of second wireless telephone  2520  then decodes the main and auxiliary channels according to one of the following two examples.  
      In a first example, for each voice frame of the transmitted signals, decoder  2670  of second wireless telephone  2520  is configured to estimate channel impairments. A channel is corrupted if the estimated channel impairments for that channel exceed a threshold. If (i) the main channel is corrupted by channel impairments, and if (ii) at least one of the auxiliary channels is not corrupted by channel impairments, then the decoder is configured to decode one of the auxiliary channels to produce the output signal.  
      In a second example, decoder  2670  uses the main channel and one of the auxiliary channels to improve the performance of a frame erasure concealment algorithm. Frame erasure occurs if the degree of channel impairments in a given voice frame exceeds a predetermined threshold. Rather than output no signal during a voice frame that has been erased, which would result in no sound during that voice frame, some decoders employ a frame erasure concealment algorithm to conceal the occurrence of an erased frame. A frame erasure concealment algorithm attempts to fill the gap in sound by extrapolating a waveform for the erased frame based on the waveform that occurred before the erased frame. Some frame erasure concealment algorithms use the side information (e.g., predictor coefficients, pitch period, gain, etc.) to guide the waveform extrapolation in order to successfully conceal erased frames. An example frame erasure concealment algorithm is disclosed in U.S. patent application Ser. No. 10/968,300 to Thyssen et al., entitled “Method For Packet Loss And/Or Frame Erasure Concealment In A Voice Communication System,” filed Oct. 20, 2004, the entirety of which is incorporated by reference herein.  
      In this second example, for each voice frame of the transmitted signals, decoder  2670  is configured to estimate channel impairments. If (i) the side information of the main channel is corrupted, and if (ii) the corresponding side information of at least some of the auxiliary channels channel is not corrupted, then decoder  2670  is configured to use both the main channel and one of the auxiliary channels to improve performance of a frame erasure concealment algorithm in the production of the output signal. By using uncorrupted side information from one of the auxiliary channels, the frame erasure concealment algorithm can more effectively conceal an erased frame.  
     XI. Improved Channel Decoding  
      As described above, a multiple-description transmission system can be used to combat transmission channel impairments. In addition to the several advantages and embodiments mentioned above, the multiple-description transmission system can also provide improved channel decoding. However, before describing embodiments that can improve channel decoding, a brief overview of forward error correction (FEC) techniques is given.  
      A. Overview of Forward Error Correction  
      A wireless voice signal can be corrupted during transmission between wireless telephones. Often FEC techniques are employed to correct errors that occur due to the corruption of transmitted signals. To implement an FEC technique, operations must be performed on both the encoding and decoding sides of the wireless communications process. On the encoding side, an FEC technique adds redundant information to data that is to be transmitted over a channel. By using this redundant information, transmission errors can be corrected. The process of adding the redundant information to the data is called channel encoding. For example, as mentioned above with reference to  FIG. 1A , channel encoder  105  of transmit path  100  can add redundant information to digitized bits that are to be transmitted to another telephone. As is well-known in the art, convolutional coding is a common way to add redundant information to the data being transmitted to achieve FEC. A convolutional encoder makes the adjacent transmitted data symbols inter-dependent.  
      On the decoding side, one method for decoding convolutionally encoded data is maximum-likelihood sequence estimation (MLSE) that performs soft decisions while searching for a sequence that minimizes a distance metric in a trellis that characterizes the memory or inter-dependence of the transmitted data symbols. As is well-known in the art, the Viterbi algorithm is typically used in channel decoding to reduce the number of possible sequences in the trellis search when new symbols are received. For example, a Viterbi algorithm could be implemented within channel decoder  125  of  FIG. 1B .  
      During the channel decoding process, a typical Viterbi algorithm receives the digitized bits of each speech frame. If no errors occurred, the digitized bits received by the Viterbi algorithm for a particular speech frame would exactly represent the state of the encoder in encoding that speech frame. However, since errors are likely to occur, the digitized bits received by the Viterbi algorithm may not be representative of the message encoded by the encoder. Accordingly, the Viterbi algorithm attempts to select a sequence of bits that most likely represent the state of the encoder in encoding the message. In this way, if the Viterbi algorithm is successful in selecting a bit sequence that is representative of that used to encode the message, the errors that occurred during the transmission of the message would be corrected. The Viterbi algorithm begins this error correction process by developing a list of candidate bit sequences that potentially represent the intended message.  
       FIG. 28A  depicts a first candidate path  2801  (bit sequence) through a trellis,  FIG. 28B  depicts a second candidate path  2803  (bit sequence) through the trellis, and  FIG. 28C  depicts a third candidate path  2805  (bit sequence) through the trellis. Each candidate path may have a distance measure (or cost function). The conventional Viterbi algorithm selects the path with the lowest distance measure (or cost function).  
      As mentioned above, the Viterbi algorithm selects the optimal bit sequence based on a minimization of the distance between successive states of a given speech frame—i.e., the optimal bit sequence is selected based on characteristics of the digitized bits. In other words, in a typical Viterbi algorithm, the selection of the most likely message encoded by the encoder has nothing to do with the characteristics of the speech that the message represents. In contrast to a typical Viterbi algorithm, an embodiment of the present invention can use redundancy in the multiple-description transmission of a speech signal to improve channel decoding.  
      B. Example Embodiments  
      As mentioned above, a multiple-description transmission system in accordance with an embodiment of the present invention transmits multiple versions of the channel encoded digitized bits. For example,  FIG. 25  illustrates multiple signals  2550 A-B being transmitted between first wireless telephone  2510  and second wireless telephone  2520 . An embodiment of the present invention can use redundancy in the multiple versions to improve channel decoding. In another embodiment, redundancy in certain parameters of speech can also be used to improve channel decoding.  
      In U.S. Patent Application Publication No. 2006/0050813, “Method and System for Decoding Video, Voice, and Speech Data Using Redundancy,” by A. Heiman and M.-S. Arkady, a method is described where the physical constraints of a speech signal, such as the continuity of certain speech parameters (e.g. gain, pitch period, and line spectrum pairs (LSPs), etc.) from frame to frame, are used to help identify an optimal bit sequence from many candidate sequences in a typical Viterbi algorithm trellis search. The entirety of U.S. Patent Application Publication No. 2006/0050813 is incorporated by reference herein. In the example embodiments of the present invention, the inherent redundancy in such speech parameters due to multiple description transmission of the speech signal is used either alone or together with the physical constraints from frame to frame to help identify an optimal bit sequence from many candidate sequences in a Viterbi search.  
       FIG. 29  is a functional block diagram of a receive path  2900  that can be used in a first embodiment of the present invention. Receive path  2900  includes a receiver module  2902 , a channel decoder  2904 , a speech decoder  2906 , and a speaker  2908 .  
      Receiver module  2902  receives a plurality of versions of a voice signal. For example, as shown in  FIG. 30 , receiver module  2902  can receive a first voice signal  3010 A, a second voice signal  3010 B, and a third voice signal  3010 C. Each version of voice signals  3010  includes a plurality of speech frames labeled speech frame  1  through speech frame N. For each version of voice signal  3010 , commonly labeled speech frames represent time aligned speech frames. For example, speech frame  2  for voice signal  3010 A, speech frame  2  for voice signal  3010 B, and speech frame  2  for voice signal  3010 C are samplings of sounds that occurred over substantially identical durations of time. Speech frames that occur over substantially identical durations of time are referred to herein as corresponding speech frames. Thus, for example, speech frame  2  for voice signal  3010 A is a corresponding speech frame to speech frame  2  for voice signal  3010 B.  
      Channel decoder  2904  is configured to decode a speech parameter associated with a speech frame of one of the plurality of versions of the voice signal. For example, channel decoder  2904  can decode a speech parameter in speech frame  2  from first voice signal  3010 A. As described above, decoding the speech parameter includes selecting an optimal bit sequence from a plurality of candidate bit sequences. That is, channel decoder  2904  can implement a Viterbi algorithm in the channel decoding process. However, in this embodiment the selection of the optimal bit sequence is also based in part on a corresponding speech frame from another version of the voice signal. For example, in addition to speech frame  2  from first voice signal  3010 A, channel decoder  2904  can use information from speech frame  2  from second voice signal  3010 B and/or speech frame  2  from third voice signal  3010 C in the selection of the optimal bit sequence.  
      By using information from the corresponding speech frame from another version of the voice signal, channel decoder  2904  can use redundancy inherent in the multiple-description transmission to improve the selection of the optimal bit sequence. That is, each of the multiple versions of the voice signal transmitted between the first and second telephone will be affected differently by channel impairments. However, the underlying parameters (e.g. pitch period, gain, and LSPs) of the multiple versions of the transmitted speech signal should be substantially similar for speech frames that cover substantially identical time period. Therefore, if a decoding system such as the one described in the aforementioned U.S. Patent Application Publication No. 2006/0050813 is used to decode each of the multiple versions of the speech signal, then, when decoding one of the speech parameters in one of the received speech signal versions, the same speech parameters in a corresponding speech frame in other received speech signal versions can be used to help select the correct speech parameter.  
      For example, some of the bits corresponding to the pitch period parameter in speech frame  2  of the first voice signal  3010 A may be corrupted by channel impairments; whereas, the corresponding bits in speech frame  2  of the second voice signal  3010 B and/or third voice signal  3010 C may not be corrupted. However, since signals  3010 A,  3010 B, and  3010 C are just multiple description versions of the same underlying speech signal spoken at the transmitter side, given a particular voiced speech frame, these three versions of the speech signal should have pitch period parameters that are either identical or very close to each other. Therefore, there is tremendous redundancy between the same speech parameters in corresponding speech frames of the multiple received versions of the speech signal. By exploiting such speech parameter redundancy across multiple received versions of the speech signal in addition to exploiting the “physical constraints” of the same speech parameter in successive frames in time (as is done in the system described in the aforementioned U.S. Patent Application Publication No. 2006/0050813), one can achieve even more reliable channel decoding of the speech signal than is possible by exploiting the “physical constraints” alone. In the example above, by using the pitch period information from speech frame  2  of the received speech signals  3010 A,  3010 B, and  3010 C, channel decoder  2904  can more reliably select an optimal bit sequence that is representative of the encoded message. The same idea can be applied to other speech parameters such as the gain and the LSPs.  
      Referring again to  FIG. 29 , after channel decoder  2904  selects an optimal bit sequence for the speech parameter, speech decoder  2906  decodes at least one of the plurality of versions of the voice signal based on the speech parameter to generate an output signal. Speaker  2908  receives the output signal and produces a sound pressure wave corresponding thereto.  
      In the first embodiment, channel decoder  2904  selects the optimal bit sequence based in part on the corresponding speech frame from another version of the voice signal. In a second embodiment of the present invention, channel decoder  2904  selects the optimal bit sequence based (i) in part on the corresponding speech frame from the other version of the voice signal and (ii) in part on a previous speech frame from at least one of the plurality of versions of the voice signal. For example, in the first embodiment the selection of the optimal bit sequence for speech frame  2  of first voice signal  3010 A can be based on speech frame  2  from second signal  3010 B and/or third signal  3010 C. In the second embodiment, this selection can also be based on, for example, information in speech frame  1  from voice signals  3010 A,  3010 B, and/or  3010 C. In this way, “physical constraints” of the speech parameters can be used in addition to the redundancies in the speech parameters to improve the selection of the optimal bit sequence.  
      That is, some speech parameters—including, but not limited to, pitch period, gain, and spectral envelop shape—have an inherent redundancy due to the manner in which the speech parameters are generated during natural speech. For example, pitch period is a speech parameter that varies relatively slowly over time—i.e., it does not change abruptly during voiced segments of speech. Such a physical constraint is a form of redundancy. By examining the value of these speech parameters in previous speech frames, channel decoder  2904  can use this redundancy to make a better selection of the optimal bit sequence. For instance, if the value of the pitch period in speech frame  1  for each of voice signals  3010  is very different from the value of the pitch period in speech frame  2  of first voice signal  3010 A and frame  2  is in a voiced segment of speech, it is an indication that the information in speech frame  2  of first voice signal  3010 A is probably corrupted. Based on this indication, channel decoder  2904  can use more reliable information (i.e., uncorrupted information) from speech frame  2  of second voice signal  3010 B and/or third voice signal  3010 C in its selection of the optimal bit sequence.  
      C. Example Method  
       FIG. 31  is a flowchart  3100  illustrating a method for improving channel decoding in a multiple-description transmission system in accordance with an embodiment of the present invention. Flowchart  3100  begins at a step  3110  in which a plurality of versions of a voice signal are received, wherein each version includes a plurality of speech frames. For example, receiver module  2902  can receive the plurality of versions of the voice signal, which can be similar to voice signals  3010 .  
      In a step  3120 , a speech parameter associated with a speech frame of one of the plurality of versions of the voice signal is decoded. Decoding the speech parameter associated with the speech frame includes selecting an optimal bit sequence from a list of candidate bit sequences, wherein the selection of the optimal bit sequence is based in part on a corresponding speech frame from another version of the plurality of versions of the voice signal. In addition, selection of the optimal bit sequence can also be based on a previous speech frame from at least one of the plurality of versions of the voice signal.  
      In a step  3130 , at least one of the plurality of versions of the voice signal is decoded based on the speech parameter to produce an output signal. For example, referring to  FIG. 30 , speech decoder  2906  can decode at least one of first voice signal  3010 A, second voice signal  3010 B, and/or third voice signal  3010 C to produce the output signal.  
      In a step  3140 , a sound pressure wave corresponding to the decoded output signal is produced. For example, the sound pressure wave can be produced by speaker  2908 . Additionally, as would be understood by a person skilled in the relevant art(s), a power amplifier can be used to amplify the decoded output signal before it is converted into a sound pressure wave by the speaker.  
     XII. Conclusion  
      The specifications and the drawings used in the foregoing description were meant for exemplary purposes only, and not limitation. It is intended that the full scope and spirit of the present invention be determined by the claims that follow.