Patent Publication Number: US-2007121926-A1

Title: Double-talk detector for an acoustic echo canceller

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS  
      Not Applicable  
     STATEMENT OF FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT  
      Not Applicable  
     BACKGROUND OF THE INVENTION  
      1. Technical Field  
      This invention relates in general to telecommunication circuits and, more particularly, to a double-talk detector for an acoustic echo canceller.  
      2. Description of the Related Art  
      In telephone communication, and particularly in mobile phones, the clarity of a conversation is of significant importance. There are many factors that contribute to unintended noise during a conversation; one primary factor is echoing.  
       FIG. 1  illustrates the cause of echoing. Whenever a loudspeaker sits near a microphone, such as in a telephone, some part of the downlink far end signal (FES) is reflected from the loudspeaker  10  to the microphone  12 . The various reflections are referred to as the “echo path” or “channel”. Sound from the echo channel is added to the near end signal (NES) in the uplink. This acoustic phenomenon is due to the multiple reflections of the loudspeaker output signal in the near end speaker environment.  
      The multiple reflections at the near end are transmitted back to the far end. Thus, the user at the far end hears his voice delayed and distorted by the communication channel—this is known as the echo phenomenon. The longer the channel delay and the more powerful the reflections, the more annoying the echo becomes in the far end, until it makes the natural conversation impossible.  
       FIG. 2  illustrates a basic block diagram of a prior art scheme to improve the audio service quality by reducing the effect of acoustic echoing, a signal processing module, the Acoustic Echo Canceller (AEC)  14 , is currently implemented in the mobile phones.  
      In operation, the AEC  14  is an adaptive finite impulse response (AFIR) filter which mathematically mimics the echo channel. Thus, as shown in  FIG. 2 , for an echo channel which can be described by function H(z), the resultant acoustic echo is y(n). The AEC  14  defines a mathematical model, Ĥ(z), of the echo channel. The AEC  14  receives the far end signal s(n) and generates a correction signal ŷ(n). The output of the microphone, v(n), includes the echo channel, y(n), the users voice, u(n), and noise, n 0 (n). The output of the AEC  14  (the echo correction signal ŷ(n)) is mixed with the near end signal (the output of microphone  12 ) at mixer  16 . So long as ŷ(n) is a close approximation to y(n), the AEC  14  will eliminate or greatly reduce the affects of the echo channel at the uplink. It should be noted that the various signals described herein are digital signals, and are processed in digital form. It also should be noted that while the specification shows ŷ(n) being subtracted from the near end signal at mixer  16 , the output of AEC  14  could be −ŷ(n), and thus the output of AEC  14  could be added with the near end signal at mixer  16  with the same result.  
      The AEC  14  is an adaptive filter. The echo compensated signal e(n) is fed back to the AEC  14 . The AEC  14  adjusts the weights (also referred to as “taps” or “coefficients”) of the mathematical model Ĥ(z) responsive to the feedback to more closely conform to the actual acoustics of the echo channel. Methods of updating the weights are well known in the art, such as NLMS (Normalized Least Mean Square) adaptation or AP (Affine Projection) algorithm. Theoretically, the acoustic echo cancellation problem can be seen as the identification and the tracking of an unknown time varying system.  
      However, when the near end speaker and the far end speaker are talking at the same time, the adaptation of the AEC  14  is disturbed because the near end signal is uncorrelated with the far end signal. Consequently, the adaptive digital linear filter diverges far from the actual impulse response of the system echo channel H(z) and the AEC  14  no longer efficiently removes the echo in the uplink. Moreover, the near end speech signal is distorted by ŷ(n) and the quality of the communication is highly degraded by the AEC  14 .  
       FIG. 3  illustrates a basic block diagram of a prior art system to prevent the AEC divergence during the double talk situations. This embodiment uses an additional component, the Double-Talk Detector (DTD)  18 , in conjunction with the AEC  14 . The purpose of the DTD  18  is to detect double-talk situations to deliver a command signal which freezes or slows down the AEC adaptation during the double-talk situation. Hence, based on the received far end signal, s(n), and the near end signal, v(n), the DTD determines whether a double talk situation is present. If so, the AEC  14  is notified. The AEC  14  includes and adaptation algorithm,  21 , which under normal situations adapts the weights of filter  22 , which implements Ĥ(z), based on the received far end signal, s(n), and the echo compensated signal e(n). Once a double-talk situation is detected further adaptations to the weight vector for filter  14  are halted or attenuated.  
      A system of the type shown in  FIG. 3  requires significant resources. The conventional solutions in the temporal domain are generally based on energy power estimates, such as described in U.S. Pat. No. 6,608,897 or cross-correlation criterion using the uplink, downlink and the AEC error signal (Double-Talk Detection Statistic), as described in U.S. Pat. Pub. 2002/126834. In the frequency domain, the spectral or the energy distance between the far end signal and the near end signal criterion is used in U.S. Pat. Pub. 2003/133,565. In this publication, the double-talk detector signal is mainly used to freeze or to reduce the AEC adaptation during the double-talk situations.  
      Another solution in the time domain, shown in U.S. Pat. No. 6,570,986, uses multiple filters and selects one or the other filter from which to calculate a squared norm from an entire filter weight vector, depending upon the current state.  
      The prior art methods are processing intensive and subject to errant detections as the phone is moved. Therefore a need has arisen for an efficient and accurate method and apparatus for echo cancellation in view of double talk situations.  
     BRIEF SUMMARY OF THE INVENTION  
      In a first aspect of the present invention, wherein a far end signal received by a telephonic device is acoustically coupled to a near end signal transmitted by the telephonic device, echo noise is canceled by generating a first echo cancellation signal from the far end signal in an adaptive impulse response filter and generating a second echo cancellation signal from the far end signal in a non-adaptive impulse response signal using weights received from the adaptive impulse response filter. Either a single talk state or a double talk state is detected in the near end signal and either the first echo cancellation signal or the second cancellation signal is applied to the near end signal responsive to the detected state.  
      This aspect of the invention allows the adaptive filter to remain adaptive and divergent during double talk periods for simplified determination of double talk situations using the weights of the adaptive IR filter.  
      In a second aspect of the present invention, wherein a far end signal received by a telephonic device is acoustically coupled via an echo path to a near end signal transmitted by the telephonic device, a double talk state is detected by generating a first echo cancellation signal from the far end signal in an adaptive impulse response filter, wherein said adaptive impulse response filter has weights that are modified responsive to an echo compensated signal mixing the near end signal with the first echo cancellation signal. An approximation of an impulse response energy gradient using a portion of the weights is calculated and a detection signal indicating either a double talk or a single talk state is generated responsive to the approximation.  
      This aspect of the invention provides for determination of double talk situations using simplified mathematical and logical operations conducive to implementation by a DSP (digital signal processor). Also, this aspect of the invention discriminates between double talk situations and echo path variations, where divergence between the adaptive filter weights and an accurate echo path model occur due to changes in the echo path.  
    
    
     BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS  
      For a more complete understanding of the present invention, and the advantages thereof, reference is now made to the following descriptions taken in conjunction with the accompanying drawings, in which:  
       FIG. 1  illustrates causes of acoustic echoing in a communication system;  
       FIG. 2  illustrates a basic block diagram of a prior art scheme to improve the audio service quality by reducing the effect of acoustic echoing;  
       FIG. 3  illustrates a basic block diagram of a prior art system to prevent the AEC divergence during the double talk situations;  
       FIG. 4  illustrates a block diagram of an embodiment of the present invention;  
       FIG. 5  illustrates a three dimensional graph illustrating impulse responses for a NLMS filter during single talk and double talk situations;  
       FIG. 6  illustrates a three dimensional graph showing impulse responses for an auxiliary filter used in the circuit of  FIG. 4 ;  
       FIG. 7  illustrates a graph showing AEC output and DTD detection in the circuit of  FIG. 4 ; and  
       FIG. 8  illustrates a telephone using the AEC system of  FIG. 4 .  
    
    
     DETAILED DESCRIPTION OF THE INVENTION  
      The present invention is best understood in relation to  FIGS. 1-8  of the drawings, like numerals being used for like elements of the various drawings.  
       FIG. 4  illustrates an embodiment of an echo cancellation circuit  20  which substantially improves echo cancellation over the prior art. As before, the echo channel is represented by H(z), and an AEC (AFIR) filter  22  receives the far end signal s(n) and generates an echo correction signal ŷ(n) which is subtracted from v(n) at mixer  16   a . The output of mixer  16   a  is the echo compensated signal, e(n). An auxiliary filter  24  receives the far end signal s(n) and generates an echo correction signal {tilde over (y)}(n) which is subtracted from v(n) at mixer  16   a  to produce echo compensated signal {tilde over (e)}(n). Auxiliary filter  24  periodically receives and stores the AEC adapted impulse response weights corresponding to Ĥ(z) through the double talk detector (DTD)  26 . Auxiliary filter  24  is updated only during single-talk periods, as detected by DTD  26 . DTD.  26  uses the weight vector from filter  22  to detect double talk and single talk situations. Depending upon whether a single talk or a double talk situation is detected, DTD  26  selects either e(n) or {tilde over (e)}(n) for output.  
      In operation, filter  22  operates adaptively, i.e., responsive to e(n), regardless of whether a single talk or double talk situation exist. DTD  26  continuously calculates a decision signal based solely on the weight components of the weight vector of filter  22  to determine whether the present state is of v(n) is single talk or double talk. During single talk periods, d(n) is set to select e(n) for output and, periodically, the weight vector of filter  22  is stored to filter  24 . During double talk periods, d(n) is set to select {tilde over (e)}(n) for output; during this time the weight vector for filter  24  is static; but the weight vector for filter  22  will continue to be adaptive to e(n), and, hence, diverging due to the double talk. Thus, during double talk situations, {tilde over (H)}(z) is static at the point of the last transfer of a weight vector from Ĥ(z). When DTD  26  detects a transition from a double talk situation to a single talk situation, the weight vector from filter  24  is stored in filter  22  to return Ĥ(z) to a value which should be close to H(z).  
       FIG. 5  illustrates an impulse response for a NLMS AFIR filter  22  during a transition from a single talk state to a double talk state and back to single talk state. As can be seen, there is a severe disturbance induced by the double talk situation on the impulse response.  
       FIG. 6  illustrates the impulse response for a static IF filter  24  during a transition from a single talk state to a double talk state and back to single talk state. As can be seen, when a double talk situation is detected, the static auxiliary filter  24  has a non-divergent impulse response for performing echo cancellation.  
      As discussed above, the DTD  26  uses the IR energy gradient from AEC filter  22  to detect double talk situations. In the preferred embodiment, the DTD  26  uses only the second-half IR weights (i.e., the higher order weights) to perform the detection function. An energy gradient is approximated using a differential method and its absolute value is subjected to a low-pass iterative IIR (infinite impulse response) filter. The double talk decision is then made through a comparison between the decision signal and a predefined threshold. An embodiment for performing the detection is given below.  
      In the following equations, ĥ(n) is the AEC IR weight vector corresponding to the transfer function Ĥ(z), computed at the sampling time t n =t 0 +nT e , where the initial time is t 0  and the sampling period is T e .  
      ĥ(n)=[ĥ 0 , . . . ,ĥ N−1]   T ∈z, 900   N×1 , where N is the AEC IR length and z, 900   N×1  denotes the real values in a vector of length N.  
      The AEC second-half IR energy at iteration n is computed as:  
           ɛ     h   ^       ⁡     (   n   )       =       ∑     i   =     N   2         N   -   1       ⁢         h   ^     i   2     ⁡     (   n   )             
 
      The AEC IR gradient energy at iteration n is approximated using the differential energy with iteration n−1:
 
γ ĥ ( n )=|ε ĥ ( n )−ε ĥ ( n− 1)|
 
      The approximate gradient γ ĥ  is low-pass filtered to obtain the double-talk detector decision signal δ:  
      δ(n)=λδ(n−1)+(1−λ)γ ĥ (n), with λ being a constant forgetting factor, generally between the values of 0.9 and 0.99 that allows the low pass filtering to be implemented in an iterative manner.  
      The double talk decision, d(n) at iteration n is decided using a comparison between the signal values βδ(n), where β is a gain factor, with a predefined decision threshold θ according to:  
             {               d   ⁡     (   n   )       ≠   0     ,         if   ⁢           ⁢     βδ   ⁡     (   n   )         ≥   θ     ⇒     double   -     talk   ⁢           ⁢   situation                         d   ⁡     (   n   )       =   0     ,         if   ⁢           ⁢     βδ   ⁡     (   n   )         &lt;   θ     ⇒     single   -     talk   ⁢           ⁢   situation                       
 
      An example of the AEC output, AEC IR energy gradient and double talk decision are shown in  FIG. 7 .  
      The uplink signal, x(n), is selected from either the AEC IR filter  22  or the static auxiliary filter  24  dependent upon d(n):  
             {             x   ⁡     (   n   )       =           e   ^     ⁡     (   n   )       ⁢           ⁢   if   ⁢           ⁢     d   ⁡     (   n   )         =   1                   x   ⁡     (   n   )       =         e   ⁡     (   n   )       ⁢           ⁢   if   ⁢           ⁢     d   ⁡     (   n   )         =   0                   
 
      Because the DTD  26  approximates the energy gradient along the time dimension of the impulse response energy along the taps dimension, rather than the full gradient energy, the computations needed to compute the double talk decision has a low computation complexity, using only multiply, accumulate and logical operations. The embodiment described above does not need the near end signal or far end signal to detect double talk situations. Further, the complexity of computation is reduced by using only the second half of the AEC IR weight vector. More complex operations, such as divisions and matrix inversions, are not necessary. This lends the computation to a DSP (digital signal processor) fixed point implementation. Further, the computation can be implemented in both sample-to-sample and block processing.  
      While described in connection with an NLMS adaptive IR filter, the embodiment could be used with LMS (Least Mean Square), AP (Affine Projection), or other filter in the temporal domain using an IR computation.  
       FIG. 8  illustrates a telephonic device, such as a mobile phone or smart phone, incorporating the AEC system  20  of  FIG. 4 .  
      The various components of the AEC system  20 , including AEC filter  22 , auxiliary filter  24 , DTD  26  and mixers  16   a  and  16   b  can be implemented as multiple tasks on a single DSP.  
      In tests using a recorded database with artificial and real speech signals and propagation in real reverberant environments, the embodiment has shown to be noise resistant within a 5 to 20 db signal-to-noise ratio in both the uplink and the downlink. Also, this embodiment has the ability to discriminate between double-talk situations and echo path variations (EPVs). In an EPV, the echo path has changed, because the phone has moved, and thus Ĥ(z) must be modified to accommodate the new H(z). However, if an EPV is mistakenly etected as a double talk situation, the AEC filter  14  will be frozen (prior art) or the static auxiliary filter  24  is used for echo cancellation as described in connection with  FIG. 4 . In either case, mistaking an EPV for a double talk situation will delay cancellation of the echo adaptively.  
      Using the detection method described above, where only the second half of the AEC impulse response along the time dimension is used, EPVs are not generally mistaken for double talk situations, since an EPV generally affects the first half of the AEC impulse response along the time dimension, i.e.,  
             ɛ     h   ^       ⁡     (   n   )       =       ∑     i   =   0         N   2     -   1       ⁢         h   ^     i   2     ⁡     (   n   )           ,       
 
 while a double talk situation affects all the impulse response along the taps dimension (as shown in  FIG. 5 ). Accordingly, the double talk detector described above is insensitive to EPVs, resulting in fewer false detections. It should be noted that while the upper half of the higher order weights are used to detect double talk situations in the preferred embodiment, it is expected that a significantly smaller number of the higher order weights could be used, such as the top quarter or eighth of the weights, with success. In general, using a smaller portion of the higher order weights will increase the insensitivity to EPVs, but may lessen the ability to recognize a double talk situation. Of course, the number of calculations decreases with the number of weights used. It would also be possible to have a programmable number of weights used in the calculation—the user or manufacturer could adjust the number of weights used as appropriate. 
 
      Although the Detailed Description of the invention has been directed to certain exemplary embodiments, various modifications of these embodiments, as well as alternative embodiments, will be suggested to those skilled in the art. The invention encompasses any modifications or alternative embodiments that fall within the scope of the Claims.