Abstract: Systems and methods of providing improved directional noise suppression in an electronic device implement a technique that specifies a direction or speaker of interest, determines the directions corresponding to speakers not lying in the direction of interest, beam forms the reception pattern of the device microphone array to focus in the direction of interest and suppresses signals from the other directions, creating beam formed reception data. A spatial mask is generated as a function of direction relative to the direction of interest. The spatial mask emphasizes audio reception in the direction of interest and attenuates audio reception in the other directions. The beam formed reception data is then multiplied by the spatial mask to generate an audio signal with directional noise suppression.

Abstract: Systems and methods of providing improved directional noise suppression in an electronic device implement a technique that specifies a direction or speaker of interest, determines the directions corresponding to speakers not lying in the direction of interest, beam forms the reception pattern of the device microphone array to focus in the direction of interest and suppresses signals from the other directions, creating beam formed reception data. A spatial mask is generated as a function of direction relative to the direction of interest. The spatial mask emphasizes audio reception in the direction of interest and attenuates audio reception in the other directions. The beam formed reception data is then multiplied by the spatial mask to generate an audio signal with directional noise suppression.

Abstract: A method, a system, and a computer program product reducing noise in audio received by at least one microphone. The method includes determining, from an audio signal received by at least one primary microphone of an electronic device, whether a user that is proximate to the electronic device is currently speaking. The method further includes, in response to determining that a user is not currently speaking, receiving a first audio using a first microphone subset from among a plurality of microphones and receiving at least one second audio using at least one second microphone subset from among the plurality of microphones. The method further includes generating a composite signal from the first audio and the second audio. The method further includes collectively processing the audio signal and the composite signal to generate a modified audio signal having a reduced level of noise.

Abstract: A method includes obtaining, by a processor, an audio echo signal and an audio desired signal from an acoustic echo correction stage of an electronic device, and converting the echo signal and the desired signal to the frequency domain. The method further includes grouping, by the processor, frequency bin results of respective frequency domain converted echo and desired signals into respective echo and desired sub-bands. A sub-band suppressor gain is estimated based on an estimated sub-band energy for the echo and desired sub-bands. The method further includes modulating the frequency domain converted desired signal to compensate for residual echo, the modulating based, at least in part, on the estimated sub-band suppressor gain, and the modulating producing a compensated frequency domain converted echo signal. The method also includes converting the compensated frequency domain converted desired signal into time domain converted audio output signal.

Abstract: A method includes obtaining, by a processor, an audio echo signal and an audio desired signal from an acoustic echo correction stage of an electronic device, and converting the echo signal and the desired signal to the frequency domain. The method further includes grouping, by the processor, frequency bin results of respective frequency domain converted echo and desired signals into respective echo and desired sub-bands. A sub-band suppressor gain is estimated based on an estimated sub-band energy for the echo and desired sub-bands. The method further includes modulating the frequency domain converted desired signal to compensate for residual echo, the modulating based, at least in part, on the estimated sub-band suppressor gain, and the modulating producing a compensated frequency domain converted echo signal. The method also includes converting the compensated frequency domain converted desired signal into time domain converted audio output signal.

Abstract: A portable device performs echo cancellation and echo suppression. An audio echo signal and an audio desired signal are obtained from an acoustic echo correction stage of the portable device. The echo and desired signals are converted to the frequency domain. Frequency bin results of the respective frequency domain converted echo and desired signals are grouped into echo and desired sub-bands. A sub-band suppressor gain is estimated based on the estimated sub-band energy for the echo and desired sub-bands. The frequency domain converted echo signal is modulated based at least in part on the estimated sub-band suppressor gain to compensate for residual echo. The compensated frequency domain converted echo signal is time domain converted into an audio output signal. The audio output signal is processed by a selected one of a voice recognition engine and a communication module transmitter.

Abstract: The present invention describes a speech enhancement method using microphone arrays and a new iterative technique for enhancing noisy speech signals under low signal-to-noise-ratio (SNR) environments. A first embodiment involves the processing of the observed noisy speech both in the spatial- and the temporal-domains to enhance the desired signal component speech and an iterative technique to compute the generalized eigenvectors of the multichannel data derived from the microphone array. The entire processing is done on the spatio-temporal correlation coefficient sequence of the observed data in order to avoid large matrix-vector multiplications. A further embodiment relates to a speech enhancement system that is composed of two stages. In the first stage, the noise component of the observed signal is whitened, and in the second stage a spatio-temporal power method is used to extract the most dominant speech component.

Abstract: The present invention describes a speech enhancement method using microphone arrays and a new iterative technique for enhancing noisy speech signals under low signal-to-noise-ratio (SNR) environments. A first embodiment involves the processing of the observed noisy speech both in the spatial- and the temporal-domains to enhance the desired signal component speech and an iterative technique to compute the generalized eigenvectors of the multichannel data derived from the microphone array. The entire processing is done on the spatio-temporal correlation coefficient sequence of the observed data in order to avoid large matrix-vector multiplications. A further embodiment relates to a speech enhancement system that is composed of two stages. In the first stage, the noise component of the observed signal is whitened, and in the second stage a spatio-temporal power method is used to extract the most dominant speech component.

Abstract: Techniques for use in improving audio quality with use of an acoustic leak compensation (ALC) system in a mobile device are described. The mobile device includes a receiver and a microphone which is acoustically coupled to the receiver. A change in a signal power of signals received at the microphone is detected. In response to the detecting, a probe signal is enabled, and a frequency response between the receiver and the microphone is estimated using the probe signal as an input. Filter coefficients of a filter are calculated based on the estimated frequency response, and the calculated filter coefficients are applied to the filter. The filter type may be selected from a plurality of filter types based on an estimated signal-to-noise ratio (SNR) of the microphone signal.

Abstract: Audio input may be received at one or more microphones of a mobile device. Based on the audio input, a change in an acoustic environment of the device, such as a change in a direction of arrival of the audio input or a degradation in a quality of acoustic echo cancellation being performed upon the audio input, may be detected. A determination may be made that the detected change coincides with a non-acoustic physical event detected using an auxiliary sensor at the mobile device. The event may for example be device motion, a new proximate object, a change in a proximity of an object, a new heat source or a change in a heat level from a known heat source. Based on the determining, a signal processor, possibly comprising an audio beamformer or echo canceller, may be recalibrated, e.g. the audio beamformer or echo canceller may be caused to reconverge.

Abstract: A telephonic device having a speakerphone function has a loudspeaker and a plurality of microphones. The plurality of microphones are coupled to a plurality of beamformers which produce a first beamform having a spatial null in the direction of the loudspeaker and a second beamform having a spatial null in the direction of near-end signals. The two beamforms are then processed to facilitate echo reduction. By comparing the beamform powers, a state of double-talk can be determined and the determination can be used to enhance echo reduction associated with speakerphone functionality.

Abstract: A telephonic device having a speakerphone function has a loudspeaker and a plurality of microphones. The plurality of microphones are coupled to a plurality of beamformers which produce a first beamform having a spatial null in the direction of the loudspeaker and a second beamform having a spatial null in the direction of near-end signals. The two beamforms are then processed to facilitate echo reduction. By comparing the beamform powers, a state of double-talk can be determined and the determination can be used to enhance echo reduction associated with speakerphone functionality.

Abstract: Techniques for use in improving audio quality with use of an acoustic leak compensation (ALC) system in a mobile device are described. The mobile device includes a receiver and a microphone which is acoustically coupled to the receiver. A change in a signal power of signals received at the microphone is detected. In response to the detecting, a probe signal is enabled, and a frequency response between the receiver and the microphone is estimated using the probe signal as an input. Filter coefficients of a filter are calculated based on the estimated frequency response, and the calculated filter coefficients are applied to the filter. The filter type may be selected from a plurality of filter types based on an estimated signal-to-noise ratio (SNR) of the microphone signal.

Abstract: Audio input may be received at one or more microphones of a mobile device. Based on the audio input, a change in an acoustic environment of the device, such as a change in a direction of arrival of the audio input or a degradation in a quality of acoustic echo cancellation being performed upon the audio input, may be detected. A determination may be made that the detected change coincides with a non-acoustic physical event detected using an auxiliary sensor at the mobile device. The event may for example be device motion, a new proximate object, a change in a proximity of an object, a new heat source or a change in a heat level from a known heat source. Based on the determining, a signal processor, possibly comprising an audio beamformer or echo canceller, may be recalibrated, e.g. the audio beamformer or echo canceller may be caused to reconverge.

Abstract: Described herein is a speech enhancement method using microphone arrays and a new iterative technique for enhancing noisy speech signals under low signal-to-noise-ratio (SNR) environments. Included is the processing of observed noisy speech both in the spatial- and the temporal-domains to enhance the desired signal component speech and an iterative technique to compute the generalized eigenvectors of the multichannel data derived from the microphone array. The entire processing is done on the spatio-temporal correlation coefficient sequence of the observed data in order to avoid large matrix-vector multiplications. Also described is a speech enhancement system having two stages. In the first stage, the noise component of the observed signal is whitened, and in the second stage a spatio-temporal power method is used to extract the most dominant speech component. In both the stages, the filters are adapted using the multichannel spatio-temporal correlation coefficients of the data.

Abstract: The present invention describes a speech enhancement method using microphone arrays and a new iterative technique for enhancing noisy speech signals under low signal-to-noise-ratio (SNR) environments. A first embodiment involves the processing of the observed noisy speech both in the spatial- and the temporal-domains to enhance the desired signal component speech and an iterative technique to compute the generalized eigenvectors of the multichannel data derived from the microphone array. The entire processing is done on the spatio-temporal correlation coefficient sequence of the observed data in order to avoid large matrix-vector multiplications. A further embodiment relates to a speech enhancement system that is composed of two stages. In the first stage, the noise component of the observed signal is whitened, and in the second stage a spatio-temporal power method is used to extract the most dominant speech component.

Abstract: The present invention describes a speech enhancement method using microphone arrays and a new iterative technique for enhancing noisy speech signals under low signal-to-noise-ratio (SNR) environments. A first embodiment involves the processing of the observed noisy speech both in the spatial- and the temporal-domains to enhance the desired signal component speech and an iterative technique to compute the generalized eigenvectors of the multichannel data derived from the microphone array. The entire processing is done on the spatio-temporal correlation coefficient sequence of the observed data in order to avoid large matrix-vector multiplications. A further embodiment relates to a speech enhancement system that is composed of two stages. In the first stage, the noise component of the observed signal is whitened, and in the second stage a spatio-temporal power method is used to extract the most dominant speech component.