Abstract:
A full duplex speakerphone system and a method of detecting a valid near-end talker component within an outgoing signal utilize a near-talker estimator that produces a near-talker energy estimate using a spectrum analysis. The near-talker energy estimate is indicative of the amount of the valid near-end talker component within the outgoing signal. Depending on the near-talker energy estimate, the system may attenuate the outgoing signal and/or incoming signal and adjust the filter process executed by an adaptive filter of the system in order to provide a clear voice communication between connected parties. In the preferred embodiment, the near-talker estimator operates with at least one processing unit to sample the outgoing signal that has been filtered, or “cancelled,” of echo by an acoustic echo canceller of the system. The energy of the echo-cancelled outgoing signal is compared to an echo energy envelope to determine whether a certain portion of the echo-cancelled outgoing signal can be attributed to a valid near-end talker. The echo energy envelope represents a potential echo return of the incoming signal in a worst case scenario that has been increased by several factors, such as an external gain, ERLE, and a preselected uncertainty factor. The energy of the echo-cancelled outgoing signal and the echo energy envelope are examined with a noise floor estimate, which is derived from the echo-cancelled outgoing signal, to produce the near-talker energy estimate.

Description:
TECHNICAL FIELD 
     The invention relates generally to voice communication systems that use a speakerphone to enable a hands-free voice communication. More specifically, the invention relates to acoustic echo cancellation techniques and full duplex speakerphone techniques that allow simultaneous reception and transmission of voice signals without significant switched loss or perceived echo. 
     DESCRIPTION OF THE RELATED ART 
     A full duplex speakerphone is a voice terminal that consists of at least one loudspeaker and at least one microphone, so that a hands-free voice communication is enabled. A full duplex speakerphone employs acoustic echo cancellation (AEC) techniques to permit simultaneous reception and transmission of speech without perceptible echo. 
     The fundamental structure of a typical full duplex speakerphone system is shown in FIG.  1 . The full duplex speakerphone (FDS) system  10  includes an attenuator  12 , a digital-to-analog (D/A) converter  14 , an amplifier  16  and a loudspeaker  18  that are coupled in series on a receive path  20 . The system also includes a microphone  22 , a second amplifier  24 , an analog-to-digital (A/D) converter  26 , a subtraction unit  28  and a second attenuation processor  30  that are coupled in series on a send path  32 . Situated between the receive path and the send path is an adaptive filter  34 . The adaptive filter and the subtraction unit define an acoustic echo canceller. The system further includes three measurement processors  36 ,  38  and  40  that are each coupled to the receive or send path and an activity detection and control (ADAC) module  42 . The measurement processor  36  is coupled to the receive path. The measurement processor  40  is coupled to the send path between the A/D converter and the subtraction unit, while the measurement processor  38  is coupled to the send path between the subtraction unit and the attenuation processor  30 . 
     When an incoming digital signal from a far-end caller is received by the system  10 , the received signal is transmitted through the attenuator  12  on the receive path  20 . The received signal is then converted by the D/A converter  14  and amplified by the amplifier  16 . The amplified analog signal is broadcast into a room by the loudspeaker  18 . Depending on the acoustic characteristics of the room, an echo of the broadcast signal is propagated through various echo paths from the loudspeaker to the microphone  22 , such as echo paths  44  and  46 . The echo may be captured along with speech from the near-end caller by the microphone, and transmitted along the output path  32  as an outgoing analog signal. The outgoing signal is first amplified by the amplifier  24  and then converted into a digital format by the A/D converter  26 . 
     Meanwhile, the adaptive filter  34  samples the original received digital signal and performs a convolution step, i.e., a computation of an estimated echo response, using the sampled signal as a reference. The estimated echo response is a predicted acoustic echo response of the system when used in a particular environment. A current estimate of the echo response is utilized to subtract echo components of the outgoing signal. The subtraction, or cancellation, of echo components is performed by the subtraction unit  28 . After subtraction, this echo-cancelled outgoing signal is fed back to the adaptive filter  34  as an error signal that is utilized to dynamically adjust the filter coefficients that are used by the adaptive filter to execute the echo cancellation. The echo-cancelled outgoing signal is transmitted to the far-end caller via the attenuation processor  30 . Since there will usually be some residual echo, the attenuation processor is typically used to reduce the residual echo to an acceptable level. The attenuation processor can take the form of a device commonly known as the center clipper. 
     The quality of the echo cancellation depends on the ability of an adaptation algorithm, which is utilized by the adaptive filter  14 , to accurately model the true echo response. The true echo response is estimated by an adaptation process in which the error signal drives the adaptation algorithm to update the coefficients of the model, so that the error signal is driven toward zero, i.e., the echo-cancelled outgoing signal does not contain any detectable echo residue. However, the acoustic response of a room does not remain constant over time. For example, positional shifts of persons and/or the microphone in the room, or opening and closing of a door change the echo paths. The change in echo paths results in a new echo response that is inaccurately represented by the previously estimated echo model. Until the echo canceller can adapt to the new echo response, a substantial amount of echo may be transmitted to the far-end caller. 
     In addition to the echo cancellation, the system  10  is configured to determine if the signal activity is in one of four states: idle, far-end active, near-end active, or double-talk. If the far-end is active, the adaptive filter  34  should be allowed to further adapt, and the echo-cancelled outgoing signal may need to be suppressed by the attenuation processor  30 . However, if the echo-cancelled outgoing signal is mostly composed of valid near-end talker speech, then the activity state is in either the near-end active or double-talk state. In such state, the adaptive filter should be disabled and the send path attenuation should be set close to unity. This determination of the activity state is executed by the ADAC module  42 . The ADAC module examines the received signal, the original outgoing signal, and the echo-cancelled outgoing signal via the measurement processors  36 ,  38  and  40  in order to determine the composition of the echo-cancelled outgoing signal. 
     In general, the conventional detection algorithm utilized by the ADAC module  42  to differentiate between the near-end talker speech and residual echo is based on ad hoc detection techniques. Most conventional implementations teach that a correlation measure is computed between the received signal and the error signal, i.e., the echo-cancelled outgoing signal. The correlation measure may be by time domain correlation or by frequency domain correlation. The correlation algorithm seeks to determine how much the error signal matches the received signal that was broadcast by the loudspeaker. If the error signal looks substantially similar to the received signal, the send signal is considered to be composed of mostly residual echo and only far-end activity is declared. However, if the error signal looks significantly different from the received signal, the send signal is considered to be composed of substantial near-end talker speech and a double-talk condition is declared. 
     In practice, it is quite difficult to apply a correlation measure to compare the error signal against the received signal. Typically, the acoustic echo lasts much longer than the observation window, and further, the transfer function between the loudspeaker and the microphone is very complex. In fact, the echo signal may look substantially different from the received signal. In addition to signal distortion caused by the acoustic response of the room, the correlation is further complicated by the fact that the adaptive filter  34  may be well converged at certain frequencies, but not as well at other frequencies. Furthermore, in some speakerphone systems even the transfer function of the loudspeaker is not known with any significant degree of certainty. 
     Notwithstanding these difficulties, the identification of the signal component of valid near-end talker speech within the echo-cancelled outgoing signal is relatively easy when the adaptive filter has perfectly cancelled the echo. However, in real situations, the acoustic echo path can change much more quickly than the adaptive filter  34  can re-adapt. Until the adaptive filter can re-adapt, a significant amount of residual echo will be introduced to the outgoing signal. If this residual echo is incorrectly identified as a valid near-end talker speech, a significant amount of echo may be perceived by the far-end listener, and even worse, the adaptive filter will be inhibited from adapting. Potentially, the system  10  may enter a state in which the adaptive filter is not enabled because residual echo is mistaken by the system as a valid near-end talker speech. Consequently, further errors may continue to be made by the system until the control algorithm finally detects the repeated near-end speech events that occur simultaneously with the far-end speech events. In the meantime, a significant amount of unwanted echo will be transmitted to the far-end listener, decreasing the quality of the voice communication. 
     There exist known techniques to detect double-talk conditions, utilizing either subband or frequency domain adaptive filters. These techniques analyze the received signal as being a number of subbands or Discrete Fourier Transform (DFT) bins. Adaptation and convolution are performed on each one of these subbands or DFT bins. In general, the known techniques determine the approximate signal gain (loudspeaker to-microphone coupling) for each subband or bin, based on information from the adaptive filter to make the approximate signal gain measurement for each subband or bin. Given the gain for each subband or bin, a determination is made if there is a double-talk condition for each subband or bin. After detection of a double-talk condition, the following steps may be executed: (1) perform suppression for each subband or bin, usually by means of center-clipping; and (2) inhibit adaptation per each subband or bin. 
     A concern with these approaches is that the gain estimate for each subband or bin can vary dramatically in a matter of milliseconds. For example, if a person moves near the microphone and distorts the previously known echo path, the gain may suddenly change from a spectral null to a spectral peak. If the gain changes dramatically, it is quite possible for the detection algorithm to get stuck and persistently report an erroneous double-talk condition when, in fact, there is significant residual echo in that subband. 
     U.S. Pat. No. 5,732,134 to Sih describes a “double talk” detecting apparatus that analyzes the received signal and the original microphone signal into DFT bins in order to detect double talk. By comparing the received and microphone signals on a bin-by-bin basis and by removing the effect of the noise floor for each bin, the apparatus of Sih detects a “double talk” state for the whole band. The apparatus of Sih performs the DFT on the uncancelled original microphone signal, which has not been filtered of echo by an adaptive filter. In addition, the spectral noise estimate is derived from the same uncancelled microphone signal. A concern with the apparatus of Sih is that it uses a simple block-by-block computation of the receive signal DFT spectrum with no regard to the persistence of reverberant echo. 
     To avoid the said difficulties, what is needed is a system and a method that can reliably determine whether an outgoing signal is mostly of near-end talker signal or mostly of received signal echo in order to take an appropriate action to ensure a clear voice communication, without relying on a double-talk determination. 
     SUMMARY OF THE INVENTION 
     A full duplex speakerphone system and a method of detecting a valid near-end talker component within an outgoing signal utilize a near-talker estimator that produces a near-talker energy estimate using a spectrum analysis. The near-talker energy estimate is indicative of the amount of the valid near-end talker component within the outgoing signal. Depending on the near-talker energy estimate, the system may attenuate the outgoing signal and/or incoming signal and adjust the filtering process executed by an adaptive filter of the system in order to provide a clear voice communication between connected parties. 
     In the preferred embodiment, the near-talker estimator operates with at least one processing unit to sample the outgoing signal that has been filtered, or “cancelled” of echo by an acoustic echo canceller of the system. The near-talker estimator also samples an incoming signal. The sampled incoming and echo-cancelled outgoing signals are used to derive three energy spectrums. The first energy spectrum is the energy spectrum of the echo-cancelled outgoing signal. The second energy spectrum is the energy spectrum of an estimated noise floor, which is based on the energy spectrum of the echo-cancelled outgoing signal. The third energy spectrum is an echo energy envelope, which is based on the incoming signal. The echo energy envelope provides a threshold to determine with an adjustable degree of assurance whether a certain portion of the echo-cancelled outgoing signal can be attributed to the near-end talker, instead of noise or residual echo. The near-talker estimator examines these three energy spectrums and a computed spectrum of a preceding near-talker energy estimate in order to produce the current near-talker energy estimate. 
     The method of detecting a valid near-end talker component within an outgoing signal includes steps to generate, in parallel, the echo energy envelope, the energy spectrum of the echo-cancelled outgoing signal, and the noise floor energy spectrum. These spectrums are then further processed by the near-talker estimator to compute the near-talker energy estimate. 
     The steps to generate the echo energy envelope include a step at which the incoming signal is segmented into sampled data blocks by a first processing unit of the system. The sampling period is in the range of 6-20 milliseconds, so that the sampling window spans a portion of a typical speech phoneme. Next, Discrete Fourier Transform (DFT) is executed for each data block in accordance with one of a number of known variations of a Fast Fourier Transform (FFT) by the first processing unit. In an alternative arrangement, the segmentation and DFT may be executed as a by-product of the adaptive filter of the system. After the DFT step, a Hanning window function may be applied to the computed DFT element by a windowing unit of the near-talker estimator. 
     Next, the power is computed for each DFT bin by a power calculator of the near-talker estimator. For the purpose of this disclosure, the term “power” and “energy” are used interchangeably. These power values may be weighted, so that frequencies with more residual echo are weighted more heavily than frequencies with less residual echo. The results of the weighting are then passed through an envelope model filter of the near-talker estimator that creates an envelope for possible return echo, using a predefined model. For each bin, the model creates an envelope for the worst case echo return. The bin results are then transmitted to a first-in first-out (FIFO) buffer of the near-talker estimator to delay the bin results from the envelope model filter. Next, the maximum value for each bin is selected by surveying each element in the FIFO buffer. The results from the FIFO buffer are transmitted to a multiplying unit and are multiplied by the following factors: (1) a known or conservatively measured external gain (the nominal coupling gain between the loudspeaker and the microphone) with reference points between the incoming signal and the echo-cancelled outgoing signal; (2) a conservatively measured value for the echo canceller return loss enhancement (commonly known as ERLE); and (3) an uncertainty factor. The uncertainty factor may be an experimentally determined factor that results in good near-talker estimates with low probability of false indications. In the simplest implementation, these factors are scalars. However, this concept can easily be extended from a single scalar value to a vector to achieve a degree of optimization where there is some known variance in performance across the bins. The resulting vectors from the multiplying unit represent the echo energy envelope. 
     The steps to generate the energy spectrum of the echo-cancelled outgoing signal and the noise floor energy spectrum include segmenting the echo-cancelled outgoing signal into sampled data blocks and performing DFT by a second processing unit. Next, a Hanning window may be applied to the computed DFT elements by a second windowing unit to suppress spectral leakage between the DFT bins. The power is then computed for each DFT bin by a second power calculator. These computed power values represent the energy spectrum of the echo-cancelled outgoing signal. The computed power values from the second power calculator are further processed to derive the noise floor energy spectrum. The bin power vector of the outgoing signal power spectrum is first averaged by an averaging unit of the near-talker estimator for each frequency bin. Next, the noise floor power estimate is computed by a noise floor estimator of the near-talker estimator using a conventional noise floor estimation technique. 
     After computing the echo energy envelope, the energy spectrum of the echo-cancelled outgoing signal, and the noise floor energy spectrum, the method proceeds to compute the near-talker energy estimate. The bin values of the three energy spectrums are transmitted to a comparator of the near-talker estimator. The comparator outputs the maximum value for each bin from the following values: (1) the noise floor power estimate; (2) the decayed near-talker power estimate; and (3) the outgoing signal power minus the echo energy envelope plus the noise floor power estimate. 
     In one embodiment, these maximum values of the bins are summed by a power summation unit of the near-talker estimator. The summed value is then filtered by a track-up average-down filter to output a single near-talker power estimate. The near-talker power estimate is then transmitted to an activity detection and control (ADAC) module of the system in order for the ADAC module to take appropriate action in response to the near-talker power estimate. The near-talker power estimate is compared to a level of residual echo. The residual echo is estimated by predicting the echo cancelling performance of the adaptive filter of the system. If the near-talker power estimate is substantially greater than the residual echo estimate, the ADAC module directs an attenuation processor on a send path to allow the echo-cancelled outgoing signal to pass with little or no attenuation. However, if the residual echo estimate is comparable to or substantially greater than the near-end talker estimate, the ADAC module may inhibit the adaptive filter from adapting, or decrease the step size being used by the adaptive filter. In addition, the ADAC module may direct the attenuation processor on the send path to substantially suppress the echo-cancelled outgoing signal, so that no audible echo will be perceived by a person at the far-end. Furthermore, the ADAC module may direct an attenuator on the receive path to suppress the received signal in order to reduce the amount of echo that is introduced into the outgoing signal. 
     In alternative embodiments, the method and the system may be modified to derive multiple estimates, instead of a single total near-talker power estimate. As an example, a plurality of echo energy envelopes may be computed using different uncertainty factors. For each echo energy envelope, a unique near-talker power estimate would be produced. These near-talker estimates will vary with respect to the reliability of the estimates. As another example, a near-talker power estimate may be derived for a particular subset of bins, such as a first estimate for the low frequencies and a second estimate for the high frequencies. Some optimization in performance may be achieved by taking advantage of different masking properties of low or high frequencies. These multiple estimates can then be used by the ADAC module to control the final outgoing signal that is transmitted to the far-end party. 
    
    
     BRIEF DESCRIPTION OF THE DRAWINGS 
     FIG. 1 is a block diagram of a conventional full duplex speakerphone system. 
     FIG. 2 is a block diagram of a full duplex speakerphone system having a near-talker estimator in accordance with the present invention. 
     FIG. 3 is a graphical representation of different power spectrums that are used by the system of FIG. 2 to compute a near-talker power estimate. 
     FIG. 4 is a block diagram of the components of the near-talker estimator in accordance with the invention. 
     FIG. 5 is a flow diagram of a method of detecting a valid near-end talker component within an echo-cancelled outgoing signal in accordance with the invention. 
    
    
     DETAILED DESCRIPTION 
     With reference to FIG. 2, a full duplex speakerphone system  48  having a near-talker estimator  50  and associated processing units  52  and  54  in accordance with the invention is shown. The system also includes an activity detection and control (ADAC) module  56  that is operatively coupled to the near-talker estimator. Other components of the system are conventional components that are present in a conventional full duplex speakerphone system, such as the system  10  of FIG.  1 . Therefore, these conventional components will be identified with the same reference numerals of FIG.  1 . The system  48  includes the attenuator  12 , the digital-to-analog (D/A) converter  14 , the amplifier  16  and the loudspeaker  18  that are coupled in series on the receive path  20 . The system also includes the microphone  22 , the second amplifier  24 , the analog-to-digital (A/D) converter  26 , the subtraction unit  28  and the attenuation processor  30  that are coupled in series on the send path  32 . Furthermore, the system includes the adaptive filter  34  and the measurement processors  36 ,  38  and  40 . The adaptive filter and the subtraction unit define an acoustic echo canceller of the system  48 . 
     The inclusion of the near-talker estimator  50  allows the system  48  to determine whether an echo-cancelled outgoing signal mostly contains a near-talker signal or an echo of the received signal that was captured by the microphone  22 . The near-talker estimator utilizes a spectral analysis to estimate the energy or power of the near-talker signal. This near-talker estimate is then transmitted to the ADAC module  56  for comparison with a residual echo estimate computed by the ADAC module. Depending on the result of the comparison, the system takes an appropriate action to provide clear voice communication. If the near-end talker estimate is substantially greater than the residual echo estimate, the ADAC module directs the attenuation processor  30  on the send path  32  to allow the echo-cancelled outgoing signal to pass with little or no attenuation. However, if the residual echo estimate is comparable to or substantially greater than the near-end talker estimate, the ADAC module may inhibit the adaptive filter  34  from adapting, or may increase the step size being used by the adaptive filter. In addition, the ADAC module may direct the attenuation processor  30  to substantially suppress the echo-cancelled outgoing signal, so that no audible echo will be perceived by a person at the far-end. Furthermore, the ADAC module may direct the attenuator  12  on the receive path to suppress the received signal in order to reduce the amount of echo that is introduced into the outgoing signal by the signal coupling between the loudspeaker  18  and the microphone  22 . 
     The spectral analysis that is performed by near-talker estimator  50  of the system  48  will be described with an illustrative graph, shown in FIG.  3 . The graph of FIG. 3 shows four spectral distribution curves  58 ,  60 ,  62  and  64  that are plotted with respect to power and frequency for a given moment of time. The curve  58  represents the noise floor estimate, while the curve  60  represents the decayed near-talker estimate. In general, the decayed near-talker estimate is a fraction of the previous estimate of the near-end talker. The curve  62  represents the outgoing signal captured by the microphone that has been echo-cancelled by the adaptive filter  34  and the subtraction unit  28  of the system  48 . The curve  64  represents an echo envelope that is based on the received signal. The echo envelope provides an upper limit, or a threshold, to determine whether the outgoing signal includes a near-talker signal component. If the outgoing signal is less than the echo envelope, the outgoing signal is assumed to not include any near talker signal component. However, if the outgoing signal is greater than the echo envelope, the outgoing signal is then assumed to include the near-talker signal component. In the graph of FIG. 3, the outgoing signal energy curve  62  has two peaks  66  and  68 . The first peak  66  lies below the echo envelope. Thus, this peak is ignored as not being a result of a near-talker signal component. The second peak  68 , however, rises above the echo envelope. Thus, a portion of this peak will be used to compute the near-talker estimate. 
     In one embodiment, the near-talker estimator  50  generates a single near-talker estimate for the entire spectrum being analyzed. In this embodiment, the near-talker estimator examines the different signals in order to derive the single near-talker estimate, which is the area of the crosshatched regions, shown in FIG.  3 . The graph of FIG. 3 has been divided into four sections A, B, C and D to illustrate how the near-talker estimator will compute the single near-talker estimate. In section A, the outgoing signal curve  62  lies below the echo envelope curve  64 . In such situations, only the noise floor estimate curve  58  will be taken into consideration for the near-talker estimate computation. In section B, the outgoing signal curve also lies below the echo envelope curve. However, the decayed near-talker estimate curve  60  lies above the noise floor estimate curve. In this situation, the decayed near-talker estimate curve is considered for the near-talker estimate. In section C, the outgoing signal curve lies above the echo envelope curve. In such situations, the portion of the outgoing signal that is greater than the echo envelope and the noise floor estimate are considered for the near-talker estimate. Note that in the graph of FIG. 3, section C begins at a point where the difference between the outgoing signal and the echo envelope is greater than the difference between the decayed near-talker estimate and the noise floor estimate. This is due to the fact that the near-talker estimator only considers the outgoing signal when it is significantly greater than the echo envelope, i.e., when the difference between the outgoing signal and the echo envelope is greater than the difference between the decayed near-talker estimate and the noise floor estimate. Section D is identical to section A with respect to the amount of power that should be contributed toward the single near-talker estimate. The cross-hatched areas define the portions of the noise floor estimate, the decayed near-talker estimate, and/or the outgoing signal that are summed by the near-talker estimator to compute the single near-talker energy estimate. 
     A method of detecting a valid near-end talker component within an echo-cancelled outgoing signal in the full duplex speakerphone system  48  in accordance with the invention is illustrated by a flow diagram, shown in FIG.  5 . This method is primarily executed by the near-talker estimator  50 . Therefore, the method will be described with reference to the components of the near-talker estimator, which are shown in FIG.  4 . The near-talker estimator includes a windowing unit  70 A and a power calculator  72 A that operate to compute the energy of the incoming signal on the receive path  20  for a defined frequency spectrum, e.g., 0-4 kilohertz, and a second windowing unit  70 B and a second power calculator  72 B that operate to compute the energy of the echo-cancelled outgoing signal for the defined frequency spectrum. The near-talker estimator also includes a weighting module  74 , an envelope model filter  76 , a first-in first-out (FIFO) buffer  78 , a maximum finder  79  and a multiplying unit  80  that operate with the widowing unit  70 A and the power calculator  72 A to compute the echo energy envelope for the defined frequency spectrum. In addition, the near-talker estimator includes an averaging unit  82  and a noise floor estimator  84  that also operate with the second windowing unit  70 B and the second power calculator  72 B to generate the noise floor power estimate for the defined frequency spectrum. The remaining components of the near-talker estimator are a comparator  86 , a power summation unit  88  and a track-up average-down filter  90  that operate to derive the single near-talker power estimate from the computed energy of the outgoing signal, the noise floor power estimate, the echo energy envelope, and the decayed near-talker estimate. 
     With reference to FIG. 5, the method of detecting a valid near-end talker component within an echo-cancelled outgoing signal begins at step  92 , at which an incoming signal on the receive path  20  is segmented into sampled data blocks by the processing unit  52  of the system  48 . The sampling period is in the range of 6-20 milliseconds, so that the sampling window spans a portion of a typical speech phoneme. Next, at step  94 , Discrete Fourier Transform (DFT) is executed for each data block in accordance with one of a number of known variations of a Fast Fourier Transform (FFT) by the processing unit  52 . In an alternative arrangement, the segmentation and DFT may be executed by the adaptive filter  34 . In such arrangements, the processing unit  52  will no longer be needed by the system  48 . At step  96 , a window function is applied to the computed DFT elements by the windowing unit  70 A of the near-talker estimator  50  to suppress spectral leakage between the DFT bins. However, the windowing step  96  may be omitted if the leakage is minimal. For example, the leakage should be minimal for a typical subband filter bank design. Thus, the windowing step may be omitted for a case when the spectral results were from a subband filter bank. Preferably, the window function is a Hanning window function. For most DFT formulations, this consists of performing a three-point moving average using coefficients: (0.25, 0.5, 0.25). For some DFT formulations this may require an alternate set of coefficients: (−0.25, 0.5, −0.25). This frequency domain windowing technique is almost as efficient as performing the windowing function in the time domain. The very low frequency bins (including the DC bin) and the very high frequency bins can be eliminated to conserve memory without loss in performance. 
     After the windowing step  96 , the power is computed for each DFT bin by the power calculator  72 A, at step  98 . This computation is: 
     
       
         power=X 2  +Y 2 , 
       
     
     where the bin is represented by the complex number X+iY. For the purpose of this disclosure, the terms “power” and “energy” are used interchangeably. At an optional step  100 , the results of the received signal power computation are weighted, so that frequencies with more residual echo are weighted more heavily than frequencies with less residual echo. The optional step  100  is applicable in a situation where the transfer function between the loudspeaker  18  and the microphone  22  is known or where it is known that there are certain frequencies, such as very low frequencies, causing problems with respect to echo. 
     At step  102 , the results of the weighting are then passed through the envelope model filter  76  that creates an envelope for possible return echo, using a predefined model. This model accounts for the substantial persistence of echo as it reverberates through a room in which the loudspeaker  18  has broadcast the incoming signal. For each bin, the model creates an envelope for the worst case echo return. In general, the return echo is composed of: (1) echo that is substantially direct from the loudspeaker to the microphone and; (2) indirect echo that is substantially caused by reflections off of walls and surfaces throughout the room. If the return echo is known to be composed of mostly indirect echo, it is not necessary to model the direct echo path. However, in general, the indirect echo path must be modeled because the decay of indirect echo reflections is only about 1 dB per 10 milliseconds for a typical room. If this decayed echo is not modeled, it is possible for lingering reverberations to be mistaken for valid near-end speech. 
     An effective technique for modeling the aggregate of the direct and indirect echo is described below using a C-language pseudo-code: 
     
       
         RDirect[i]=TrackUpAveDown(RDirect[i], &amp;RWeighted[i], Cdirect); 
       
     
     
       
         RIndirect[i]=TrackUpAveDown(RIndirect[i], &amp;RWeighted[i], Cindirect); 
       
     
     
       
         REnv[i]=A*RDirect[i]+B*RIndirect[i]; 
       
     
     where: 
     RDirect[i] is the direct echo envelope; 
     RIndirect[i] is the indirect echo envelope; 
     REnv[i] is the aggregate echo envelope; 
     A is the portion of the direct echo that makes up the aggregate echo envelope; and 
     B is the portion of the indirect echo that makes up the aggregate echo envelope. 
     The function TrackUpAveDown is described by: 
     void TrackUpAveDown(float input, float*state, float coefficient) 
     { 
     *state=*state+coefficient*(input−*state); 
     if(input&gt;*state ) 
     *state=input; 
     } 
     This TrackUpAveDown function is a simple nonlinear filter that tracks the input as it is ascending and averages the input with the current filter state as the input is declining. 
     In case there is uncertainty regarding the position of the microphone  18  relative to the loudspeaker  22 , it may be necessary to create a delay aspect to the envelope to account for this uncertainty. This can be performed by delaying the bin results in a FIFO buffer. Therefore, at step  104 , the bin results are stored in the FIFO buffer  78  to delay the bin results from the envelope model filter  76 . Next, at step  106 , the maximum value for each bin is selected by surveying each bin of same index for each vector in the FIFO buffer by the maximum finder  79 . 
     At step  108 , the results from the FIFO buffer are transmitted to the multiplying unit and are multiplied by the following factors: (1) a known or conservatively measured external gain (the nominal coupling gain between the loudspeaker  18  and the microphone  22 ) with reference points between the received signal and the echo-cancelled outgoing signal; (2) a conservatively measured value for the echo canceller return loss enhancement (commonly known as ERLE), which is usually a number less than unity, but is limited to a minimum value that is practically guaranteed to be true all the time; and (3) an uncertainty factor. The uncertainty factor may be an experimentally determined factor that results in good near-talker estimates with low probability of false indications. The uncertainty factor is usually greater than unity. The resulting vectors, which represent the echo energy envelope, are transmitted to the comparator  86 . Although these factors are described as scalar numbers, this concept can easily be extended from a single scalar value to a vector to achieve a degree of optimization where there is some known variance in performance across the bins. 
     Executed in parallel to steps 92-108, an echo-cancelled outgoing signal is processed at steps 110-120 to derive an outgoing signal power spectrum and a noise floor power estimate. Similar to the processing of the received signal, the echo-cancelled outgoing signal on the send path is segmented into sampled data blocks and is transformed using DFT by the processing unit  54 , at steps  110  and  112 , respectively. Next, at step  114 , a window function is applied to the computed DFT elements by the windowing unit  70 B of the near-talker estimator  50  to suppress spectral leakage between the DFT bins. Preferably, the window function is a Hanning window function. At step  116 , the power is computed for each DFT bin by the power calculator  72 B. These computed power values represent the outgoing signal power spectrum. The outgoing signal power spectrum is transmitted to the comparator  86  to be processed along with the computed echo energy envelope. 
     In addition to being transmitted to the comparator, the outgoing signal power spectrum is transmitted to the averaging unit  82  of the near talker estimator  50  for further processing to derive the noise floor power estimate. At step  118 , the bin power vector of the outgoing signal power spectrum is averaged by the averaging unit  82  for each frequency bin. Next, at step  120 , the noise floor power estimate is computed by the noise floor estimator using a conventional noise floor estimation technique. As an example, the noise floor estimate for each bin may be computed by the following pseudo-code procedure: 
     static variables: 
     NoiseEst; 
     UpDelta; 
     Down Factor; 
     function NoiseFloorEstimate(SinputPower) 
     { 
     if(inputPower &gt;NoiseEst) 
     NoiseEst=NoiseEst+UpDelta; 
     else 
     NoiseEst=NoiseEst+DownFactor*(inputPower −NoiseEst); 
     return NoiseEst; 
     }In this procedure, the noise level estimate floats up slowly when the input power is greater than the current noise estimate. However, when the input power is less than the current noise level estimate, the estimate goes downward much faster and nearly tracks the level of the inputPower as successively lower powers are reported. The computed noise floor power estimate is transmitted to the comparator  86 . The comparator is now ready to compute the near-talker power estimate for each bin. 
     At step  122 , the comparator  86  outputs the maximum value for each bin from the following values: (1) the noise floor power estimate; (2) the decayed near-talker power estimate; and (3) the outgoing signal power minus the echo energy envelope plus the noise floor power estimate. Next, at step  124 , these maximum values of the bins are summed by the power summation unit  88 . The summed value is then filtered by the track-up average-down filter  90  to output the single near-talker power estimate, at step  126 . 
     The near-talker power estimate is transmitted to the ADAC module  56  in order for the ADAC module to take appropriate action in response to the near-talker power estimate. At step  128 , the near-talker power estimate is compared to a level of residual echo. The residual echo is estimated by predicting the echo cancelling performance of the adaptive filter  34 . If the near-talker power estimate is substantially greater than the residual echo estimate, the ADAC module directs the attenuation processor  30  to allow the echo-cancelled outgoing signal to pass with little or no attenuation. However, if the residual echo estimate is comparable to or substantially greater than the near-end talker estimate, the ADAC module may inhibit the adaptive filter from adapting, or decrease the step size being used by the adaptive filter. In addition, the ADAC module may direct the attenuation processor  30  on the send path to substantially suppress the echo-cancelled outgoing signal, so that no audible echo will be perceived by a person at the far-end. Furthermore, the ADAC module may direct the attenuator  12  on the receive path to suppress the received signal in order to reduce the amount of echo that is introduced into the outgoing signal. 
     In alternative embodiments, the method and the system may be modified to derive multiple estimates, instead of a single total near-talker power estimate. As an example, a plurality of echo energy envelopes may be computed using different uncertainty factors. For each echo energy envelope, a unique near-talker power estimate would be produced. These near-talker estimates will vary with respect to the reliability of the estimates. As another example, a near-talker power estimate may be derived for a particular subset of bins, such as a first estimate for the low frequencies and a second estimate for the high frequencies. Some optimization in performance may be achieved by taking advantage of different masking properties of low or high frequencies. These multiple estimates can then be used by the ADAC module to control the final outgoing signal that is transmitted to the far-end party.