An audio signal processing method includes: acquiring audio signals from at least two sound sources respectively through at least two microphones (MICs) to obtain respective original noisy signals of the at least two MICs in a time domain; for each frame in the time domain, using a first asymmetric window to perform a windowing operation on the respective original noisy signals of the at least two MICs to acquire windowed noisy signals; performing time-frequency conversion on the windowed noisy signals to acquire respective frequency-domain noisy signals of the at least two sound sources; acquiring frequency-domain estimated signals of the at least two sound sources according to the frequency-domain noisy signals; and obtaining audio signals produced respectively by the at least two sound sources according to the frequency-domain estimated signals.

A signal processing device applies a convolutional separation filter, which is a combined filter of: a rear reverberation removal filter for suppressing a rear reverberation component from a mixed acoustic signal obtained by converting an observed mixed acoustic signal obtained by observing a source signal into a time-frequency domain; and a sound source separation filter for emphasizing components corresponding to source signals from the mixed acoustic signal, to a mixed acoustic signal string including the mixed acoustic signal and a delay signal of the mixed acoustic signal and estimates model parameters of a model for obtaining information corresponding to signals in which the rear reverberation component is suppressed and target signals emitted from target sound sources in the source signal are emphasized.

A signal processing device applies a convolutional separation filter, which is a combined filter of: a rear reverberation removal filter for suppressing a rear reverberation component from a mixed acoustic signal obtained by converting an observed mixed acoustic signal obtained by observing a source signal into a time-frequency domain; and a sound source separation filter for emphasizing components corresponding to source signals from the mixed acoustic signal, to a mixed acoustic signal string including the mixed acoustic signal and a delay signal of the mixed acoustic signal and estimates model parameters of a model for obtaining information corresponding to signals in which the rear reverberation component is suppressed and target signals emitted from target sound sources in the source signal are emphasized.

Method and apparatus obtain information about a patient and/or a respiratory therapy system that is configured to deliver respiratory therapy to the patient. The respiratory therapy system may include a flow generator configured to generate a supply of pressurized air along an air circuit to a patient interface. A sound signal representing a sound in the air circuit may be processed to obtain cepstrum data. A time series of delay estimates based on acoustic signatures of the cepstrum data may be generated. Each acoustic signature may represent a reflection of sound from a patient interface along the air circuit. Variation in the time series of delay estimates may be analysed. One or more output indicators based on the variation may be generated. The one or more output indicators may concern patient and/or system status.

Method and apparatus obtain information about a patient and/or a respiratory therapy system that is configured to deliver respiratory therapy to the patient. The respiratory therapy system may include a flow generator configured to generate a supply of pressurized air along an air circuit to a patient interface. A sound signal representing a sound in the air circuit may be processed to obtain cepstrum data. A time series of delay estimates based on acoustic signatures of the cepstrum data may be generated. Each acoustic signature may represent a reflection of sound from a patient interface along the air circuit. Variation in the time series of delay estimates may be analysed. One or more output indicators based on the variation may be generated. The one or more output indicators may concern patient and/or system status.

A method and apparatus for determining a speech presence probability and an electronic device are provided. According to present disclosure, a metric parameter of a signal to noise ratio of a signal of a first channel and a metric parameter of a signal power level difference between the first channel and the second channel are introduced in determining the speech presence probability, the normalization and non-linear transformation processing is performed on the above-mentioned metric parameters, and the speech presence probability is obtained by fitting the product term and a first power term of a power exponent of the above-mentioned parameters. Therefore, the calculation amount of calculating the speech presence probability is reduced, the calculation result has good robustness to parameter fluctuations, and the disclosure can be widely applied to various application scenarios of dual-microphone speech enhancement systems.

An audio signal processor includes a digital filter block configured to receive an audio signal and output a first filtered audio signal, and a phase linearization block configured to receive the first filtered audio signal and output a second filtered audio signal with a more linear phase.

An audio signal processor includes a digital filter block configured to receive an audio signal and output a first filtered audio signal, and a phase linearization block configured to receive the first filtered audio signal and output a second filtered audio signal with a more linear phase.

A method for Short-Time Fourier Transform-based echo muting includes receiving a microphone signal including acoustic echo captured by a microphone and corresponding to audio content from an acoustic speaker, and receiving a reference signal including a sequence of frames representing the audio content. For each frame in a sequence of frames, the method includes processing, using an acoustic echo canceler configured to receive a respective frame as input to generate a respective output signal frame that cancels the acoustic echo from the respective frame, and determining, using a Double-talk Detector (DTD), based on the respective frame and the respective output signal frame, whether the respective frame includes a double-talk frame or an echo-only frame. For each respective frame that includes the echo-only frame, muting the respective output signal frame, and performing speech processing on the respective output signal frame for each respective frame that includes the double-talk frame.

A method for Short-Time Fourier Transform-based echo muting includes receiving a microphone signal including acoustic echo captured by a microphone and corresponding to audio content from an acoustic speaker, and receiving a reference signal including a sequence of frames representing the audio content. For each frame in a sequence of frames, the method includes processing, using an acoustic echo canceler configured to receive a respective frame as input to generate a respective output signal frame that cancels the acoustic echo from the respective frame, and determining, using a Double-talk Detector (DTD), based on the respective frame and the respective output signal frame, whether the respective frame includes a double-talk frame or an echo-only frame. For each respective frame that includes the echo-only frame, muting the respective output signal frame, and performing speech processing on the respective output signal frame for each respective frame that includes the double-talk frame.