Abstract: A signal processor for performing signal enhancement, the signal processor comprising: an input-terminal, configured to receive an input-signaling; an output-terminal; an interference-cancellation-block configured to receive the input-signaling and to provide an interference-estimate-signaling and an interference-cancelled-signal based on the input-signaling. The signal processor further comprises a feature-block configured to provide a combination-feature-signal based on the interference-cancelled-signal and the interference-estimate-signaling; and a neural-network-block configured to apply model parameters to the combination-feature-signal to provide a neural-network-output-signal to the output-terminal.

Abstract: The disclosure relates to a processing multi-channel audio signals, an example embodiment including a method of processing a multi-channel audio signal, the method comprising: determining a location of sound sources (101, 102) within the signal; applying a rotation operation to the signal, a direction of the rotation operation dependent on the location of the sound sources in the signal; and generating a rotated audio signal.

Abstract: A signal processor comprising: a modelling block, configured to receive a frequency-domain-input-signal, a fundamental-frequency-signal representative of a fundamental frequency of the frequency-domain-input-signal; and configured to provide a pitch-model-signal based on a periodic function, the pitch-model-signal spanning a plurality of discrete frequency bins, each discrete frequency bin having a respective discrete frequency bin index, wherein within each discrete frequency bin the pitch-model-signal is defined by: the periodic function; the fundamental frequency; the frequency-domain-input-signal; and the respective discrete frequency bin index. The signal processor further comprises a manipulation block, configured to provide an output-signal based on the frequency-domain-input-signal and the pitch-model-signal.

Abstract: A signal processor comprising: a signal-manipulation-block configured to: receive a cepstrum-input-signal, wherein the cepstrum-input-signal is in the cepstrum domain and comprises a plurality of bins; receive a pitch-bin-identifier that is indicative of a pitch-bin in the cepstrum-input-signal; and generate a cepstrum-output-signal based on the cepstrum-input-signal by: scaling the pitch-bin relative to one or more of the other bins of the cepstrum-input-signal; or determining an output-pitch-bin-value based on the pitch-bin, and setting one or more of the other bins of the cepstrum-input-signal to a predefined value; or determining an output-other-bin-value based on one or more of the other bins of the cepstrum-input-signal, and setting the pitch-bin to a predefined value.

Abstract: A signal processor for performing signal enhancement, the signal processor comprising: an input-terminal, configured to receive an input-signaling; an output-terminal; an interference-cancellation-block configured to receive the input-signaling and to provide an interference-estimate-signaling and an interference-cancelled-signal based on the input-signaling. The signal processor further comprises a feature-block configured to provide a combination-feature-signal based on the interference-cancelled-signal and the interference-estimate-signaling; and a neural-network-block configured to apply model parameters to the combination-feature-signal to provide a neural-network-output-signal to the output-terminal.

Abstract: A signal processor comprising: a modelling block, configured to receive a frequency-domain-input-signal, a fundamental-frequency-signal representative of a fundamental frequency of the frequency-domain-input-signal; and configured to provide a pitch-model-signal based on a periodic function, the pitch-model-signal spanning a plurality of discrete frequency bins, each discrete frequency bin having a respective discrete frequency bin index, wherein within each discrete frequency bin the pitch-model-signal is defined by: the periodic function; the fundamental frequency; the frequency-domain-input-signal; and the respective discrete frequency bin index. The signal processor further comprises a manipulation block, configured to provide an output-signal based on the frequency-domain-input-signal and the pitch-model-signal.

Abstract: The disclosure relates to a processing multi-channel audio signals, an example embodiment including a method of processing a multi-channel audio signal, the method comprising: determining a location of sound sources (101, 102) within the signal; applying a rotation operation to the signal, a direction of the rotation operation dependent on the location of the sound sources in the signal; and generating a rotated audio signal.

Abstract: A signal processor comprising: a signal-manipulation-block configured to: receive a cepstrum-input-signal, wherein the cepstrum-input-signal is in the cepstrum domain and comprises a plurality of bins; receive a pitch-bin-identifier that is indicative of a pitch-bin in the cepstrum-input-signal; and generate a cepstrum-output-signal based on the cepstrum-input-signal by: scaling the pitch-bin relative to one or more of the other bins of the cepstrum-input-signal; or determining an output-pitch-bin-value based on the pitch-bin, and setting one or more of the other bins of the cepstrum-input-signal to a predefined value; or determining an output-other-bin-value based on one or more of the other bins of the cepstrum-input-signal, and setting the pitch-bin to a predefined value.

Abstract: A device including a processor and a memory is disclosed. The memory includes programming instructions which when executed by the processor perform an operation. The operation includes detecting relative position of two earphones when connected to the device, determining if a binaural signal processing mode is appropriate based on the detected relative position and switching to the binaural signal processing mode. If it is determined that the binaural signal processing mode is not appropriate, switching to monaural processing mode.

Abstract: A device including a processor and a memory is disclosed. The memory includes programming instructions which when executed by the processor perform an operation. The operation includes detecting relative position of two earphones when connected to the device, determining if a binaural signal processing mode is appropriate based on the detected relative position and switching to the binaural signal processing mode. If it is determined that the binaural signal processing mode is not appropriate, switching to monaural processing mode.

Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.

Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.

Abstract: Sound signals captured by a microphone are adjusted to provide improved sound quality. More particularly, an Acoustic Echo Reduction system which performs a first stage of echo reduction (e.g., acoustic echo cancellation) on a received signal is configured to perform a second stage of echo reduction (e.g., acoustic echo suppression) by segmenting the received signal into a plurality of frequency bins respectively comprised within a number of frames (e.g., 0.3 s to 0.5 s sound signal segments) for a given block. Data comprised within respective frequency bins is modeled according to a probability density function (e.g., Gaussian distribution). The probability of whether respective frequency bins comprise predominantly near-end signal or predominantly residual echo is calculated.

Abstract: Sound signals captured by a microphone are adjusted to provide improved sound quality. More particularly, an Acoustic Echo Reduction system which performs a first stage of echo reduction (e.g., acoustic echo cancellation) on a received signal is configured to perform a second stage of echo reduction (e.g., acoustic echo suppression) by segmenting the received signal into a plurality of frequency bins respectively comprised within a number of frames (e.g., 0.3 s to 0.5 s sound signal segments) for a given block. Data comprised within respective frequency bins is modeled according to a probability density function (e.g., Gaussian distribution). The probability of whether respective frequency bins comprise predominantly near-end signal or predominantly residual echo is calculated.

Abstract: A multichannel acoustic echo reduction system is described herein. The system includes an acoustic echo canceller (AEC) component having a fixed filter for each respective combination of loudspeaker and microphone signals and having an adaptive filter for each microphone signal. For each microphone signal, the AEC component modifies the microphone signal to reduce contributions from the outputs of the loudspeakers based at least in part on the respective adaptive filter associated with the microphone signal and the set of fixed filters associated with the respective microphone signal.