Abstract: There are provided methods and systems for automated testing of echo cancellers using natural speech excitations and evaluating an echo canceller by transmitting a first signal to the echo canceller, wherein the first signal includes a first speech signal and a first marker signal, and wherein the first marker signal is transmitted a first period of time after the first speech signal is transmitted; receiving a second signal from the echo canceller, wherein the second signal includes a second speech signal and a second marker signal; aligning the first speech signal and the second speech signal using the first marker signal and the second marker signal; determining a choppiness of the second speech signal, when a non-linear processor of the echo canceller is on; and determining an audible echo, when a non-linear processor of the echo canceller is off.

Abstract: A method of masking a residual echo signal by an echo canceller is provided. The method comprises receiving a far-end signal, adjusting filter coefficients of an adaptive filter in response to the far-end signal, generating an echo model signal based on the far-end signal using the adaptive filter, receiving a near-end signal, subtracting the echo model signal from the near-end signal to generate an output signal, defining a spectral mask based on the near-end signal, wherein the spectral mask is indicative of near-end spectral peaks and near-end spectral valleys, de-emphasizing the output signal in spectral regions of the near-end spectral peaks, and emphasizing the output signal in spectral regions of the near-end spectral valleys, wherein the de-emphasizing occurs during filter coefficients determination for the adaptive filter. A weighted filter may perform the de-emphasizing and the emphasizing operations, where the weighted filter uses medium term spectral characteristics of the near-end signal.

Abstract: A method of adjusting an echo canceller comprises obtaining a first cross-correlation between a far-end signal and an error signal, wherein the error signal is generated by subtracting an output signal of an adaptive filter from a local-end signal; determining whether the first cross-correlation is above a pre-determined threshold; relocating the adaptive filter by a few samples if the determining determines that the first cross-correlation is above a pre-determined threshold; calculating a first improvement indicator parameter, wherein the first improvement indicator parameter is calculated after the relocating the adaptive filter by the few samples; determining whether the first improvement indicator parameter indicates a performance improvement by the adaptive filter after the relocating the adaptive filter by the few samples; calculating a gain based on the local-end signal and the error signal if the determining does not determine the performance improvement; and multiplying the adaptive filter by the ga

Abstract: A speech encoder that analyzes and classifies each frame of speech as being periodic-like speech or non-periodic like speech where the speech encoder performs a different gain quantization process depending if the speech is periodic or not. If the speech is periodic, the improved speech encoder obtains the pitch gains from the unquantized weighted speech signal and performs a pre-vector quantization of the adaptive codebook gain GP for each subframe of the frame before subframe processing begins and a closed-loop delayed decision vector quantization of the fixed codebook gain GC. If the frame of speech is non-periodic, the speech encoder may use any known method of gain quantization.

Abstract: There is provided a method for use by an echo canceller to detect an echo path change and adjust to the echo path change. The method comprises determining a first bulk delay using a SPARSE foreground adaptive filter; configuring the foreground adaptive filter to an open-loop mode; canceling the echo signal based on the first bulk delay using the foreground adaptive filter; determining a second bulk delay of the echo signal using a SPARSE background adaptive filter; configuring the foreground adaptive filter to a closed-loop mode and continuing to cancel the echo signal based on the first bulk delay; configuring the background adaptive filter to the open-loop mode; measuring echo cancellation performance of the foreground adaptive filter and the background adaptive filter; and changing parameters of the foreground adaptive filter if the echo cancellation performance of the background adaptive filter is better than the foreground adaptive filter.

Abstract: A speech encoder that analyzes and classifies each frame of speech as being periodic-like speech or non-periodic like speech where the speech encoder performs a different gain quantization process depending if the speech is periodic or not. If the speech is periodic, the improved speech encoder obtains the pitch gains from the unquantized weighted speech signal and performs a pre-vector quantization of the adaptive codebook gain GP for each subframe of the frame before subframe processing begins and a closed-loop delayed decision vector quantization of the fixed codebook gain GC. If the frame of speech is non-periodic, the speech encoder may use any known method of gain quantization.

Abstract: A method of using music detection to enhance an operation of an echo canceller is provided, wherein the echo canceller includes an adaptive filter and a nonlinear processor. The method comprises receiving an input signal including an echo signal by the echo canceller from a near end device, filtering the input signal using the adaptive filter to eliminate linear components of the echo signal in the input signal and generate an error signal, analyzing the error signal using a music detector to determine existence of a music signal in the error signal, bypassing the nonlinear processor if the analyzing determines the music signal exists in the error signal, and eliminating nonlinear components of the echo signal from the error signal using the nonlinear processor if the analyzing determines the music signal does not exist in the error signal.

Abstract: There is provided a method of detecting an infinite echo return loss (ERL) in an echo cancellation system while in a finite ERL mode. The method comprises determining a running mean attenuation by the echo cancellation system, determining a ratio of an echo signal to a near-end noise ratio (ENR), defining an infinite ERL threshold (THinfinite) as a function of the ENR, and switching to an infinite ERL mode as a function of the running mean attenuation and the THinfinite. The running mean attenuation can be enhanced echo return loss (ERLE), and the higher the ENR the higher the THinfinite and the lower the ENR the lower the THinfinite. The switching can further be a function of an energy distribution, where the switching switches to the infinite ERL mode based on a non-localized energy distribution over an echo path delay for a predetermined period of time.

Abstract: There is provided a method of decoding speech data generated from a speech signal. The method comprises receiving the speech data having at least one main pulse in a subframe of the speech data; generating a first predicted pulse, based on the at least one main pulse, on one side of the main pulse in the subframe of the speech data, wherein the first predicted pulse has a lower gain than the main pulse; generating a second predicted pulse, as a mirror image of the first predicted pulse on a reverse time scale, on the other side of the main pulse in the subframe of the speech data; reconstructing the speech signal using the at least one main pulse, the first predicted pulse and the second predicted pulse.

Abstract: There is provided a method for use by a speech encoder to encode an input speech signal.

Abstract: There is provided a method of updating a noise state of a voice activity detector (VAD) for indicating an active voice mode and an inactive voice mode. The method comprises receiving an input signal having a plurality of frames, determining an elapsed time since the last update of the noise state, updating the noise state of the VAD if the elapsed time exceeds a predetermined time, determining an average minimum energy based on two or more of the plurality of frames, determining a current minimum energy based on a current frame of the plurality of frames, updating the noise state of the VAD if the average minimum energy is less than the current minimum energy, and updating the noise state of the VAD if the average minimum energy is greater than the current minimum energy plus a first predetermined value.

Abstract: A speech encoder that analyzes and classifies each frame of speech as being periodic-like speech or non-periodic like speech where the speech encoder performs a different gain quantization process depending if the speech is periodic or not. If the speech is periodic, the improved speech encoder obtains the pitch gains from the unquantized weighted speech signal and performs a pre-vector quantization of the adaptive codebook gain GP for each subframe of the frame before subframe processing begins and a closed-loop delayed decision vector quantization of the fixed codebook gain GC. If the frame of speech is non-periodic, the speech encoder may use any known method of gain quantization.

Abstract: There is provided a speech encoding system that receives a speech signal. The speech encoding system comprises a frame processor for processing a frame of the speech signal, where the frame processor includes a pitch gain generator that derives unquantized pitch gains, and a first vector guantizer that receives the unquantized pitch gains and generates quantized pitch gains. The speech encoding system also comprises a subframe processor that begins subframe processing after the pitch gain generator has derived the unquantized pitch gains and the first vector quantizer has generated the quantized pitch gains.

Abstract: The invention improves the encoding and decoding of speech by focusing the encoding on the perceptually important characteristics of speech. The system analyzes selected features of an input speech signal, and first performing a common frame based speech coding of an input speech signal. The system then performs a speech coding based on either a first speech coding mode or a second speech coding mode. The selection of a mode is based on characteristics of the input speech signal. The first speech coding mode uses a first framing structure and the second speech coding mode uses a second framing structure.

Abstract: There is provided a voice activity detection method for indicating an active voice mode and an inactive voice mode. The method comprises receiving an input signal having a plurality of frames, determining whether each of the plurality of frames includes an active voice signal or an inactive voice signal, determining a second reflection coefficient for each frame determined to include the inactive voice signal, comparing the second reflection coefficient with a reflection threshold, and selecting the active voice mode if the second reflection coefficient is greater than the reflection threshold. The method may further comprise selecting the inactive voice mode if the second reflection coefficient is not greater than the reflection threshold. The method may also comprise analyzing the input signal to determine an energy level of the input signal, and selecting the active voice mode if the energy level is greater than an energy threshold.

Abstract: The invention improves the encoding and decoding of speech by focusing the encoding on the perceptually important characteristics of speech. The system analyzes selected features of an input speech signal, and first performing a common frame based speech coding of an input speech signal. The system then performs a speech coding based on either a first speech coding mode or a second speech coding mode. The selection of a mode is based on characteristics of the input speech signal. The first speech coding mode uses a first framing structure and the second speech coding mode uses a second framing structure.

Abstract: There are provided methods and devices for generating excitation values for a speech signal. In one aspect, an example method comprises obtaining one or more characteristics of a first speech frame of the speech signal, deriving a first seed value based on the one or more characteristics of the first speech frame, providing the first seed value to a Gaussian time series generator; and using the Gaussian time series generator to generate an excitation values for the first frame. The one or more characteristics may include a spectrum information of the first frame, an energy information of the first frame, or a gain information of the first frame.

Abstract: Speech coding systems include multi-rate speech codecs having an encoder and a decoder. Silence description coding for multi-rate speech coding systems that employ discontinued transmission is performed in either the encoder or the decoder of the multi-rate speech codec. It may also be performed in a distributed manner wherein it is performed partially in the encoder and partially in the decoder. The silence description coding is performed on a speech signal having a substantially non-speech-like characteristic. Voice activity detection classifies the speech signal as being either substantially speech-like or substantially non-speech-like. The silence description coding is selected from a plurality of coding modes. In certain embodiments of the invention, the silence description coding is a source coding mode that operates at a bit rate that fits within a bit rate budget as determined by all of the available source coding modes within the plurality of coding modes.

Abstract: There is provided a voice activity detection method for indicating an active voice mode and an inactive voice mode. The method comprises receiving a first portion of an input signal; determining that the first portion of the input signal includes an active voice signal; indicating the active voice mode in response to the determining that the first portion of the input signal includes the active voice signal; receiving a second portion of the input signal immediately following the first portion of the input signal; determining that the second portion of the input signal includes an inactive voice signal; extending the indicating the active voice mode for a period of time after determining that the second portion of the input signal includes the inactive voice signal, wherein the period of time varies based on one or more conditions; and indicating the inactive voice mode after expiration of the period of time.

Abstract: There is provided a method of updating a noise state of a voice activity detector (VAD) for indicating an active voice mode and an inactive voice mode. The method comprises receiving an input signal having a plurality of frames, determining an elapsed time since the last update of the noise state, updating the noise state of the VAD if the elapsed time exceeds a predetermined time, determining an average minimum energy based on two or more of the plurality of frames, determining a current minimum energy based on a current frame of the plurality of frames, updating the noise state of the VAD if the average minimum energy is less than the current minimum energy, and updating the noise state of the VAD if the average minimum energy is greater than the current minimum energy plus a first predetermined value.