Abstract: A method and apparatus for processing a signal. An implementation of the method includes: acquiring a reference signal of a to-be-tested voice, the reference signal being a signal output to a voice output device, where the voice output device outputs the to-be-tested voice after obtaining the reference signal; receiving, from a voice input device, an echo signal of the to-be-tested voice, the echo signal being a signal of the to-be-tested voice collected by the voice input device; performing signal preprocessing on the reference signal and the echo signal respectively; and inputting the processed reference signal and the processed echo signal into a pre-trained time delay estimation model, to obtain a time difference between the reference signal and the echo signal output by the time delay estimation model.

Abstract: Provided are a voice noise reduction method, an electronic device, and a non-transitory computer-readable storage medium. The specific implementation scheme includes determining a to-be-denoised voice spectrum of a to-be-denoised voice signal; performing feature extraction on the to-be-denoised voice spectrum to obtain a local voice spectral feature of the to-be-denoised voice spectrum; determining a global voice spectral feature of the to-be-denoised voice spectrum according to the local voice spectral feature of the to-be-denoised voice spectrum; and determining a masking matrix of an original voice signal in the to-be-denoised voice signal according to the local voice spectral feature and the global voice spectral feature, and determining the original voice signal according to the to-be-denoised voice spectrum and the masking matrix.

Abstract: A speech enhancement method includes steps as follows. Subband decomposition processing is performed on at least two paths of target speech to obtain amplitude spectrums and phase spectrums of the at least two paths of target speech, where the at least two paths of target speech include: target mixed speech and target interference speech; a prediction probability of the target mixed speech including target clean speech in a feature domain is determined according to the amplitude spectrums of the at least two paths of target speech; and subband synthesis processing is performed according to the prediction probability and the amplitude spectrums and the phase spectrums of the at least two paths of target speech to obtain the target clean speech in the target mixed speech.

Abstract: Provided are a voice activity detection method and apparatus, an electronic device and a storage medium, which relate to the technical field of voice processing, for example, to the technical field of artificial intelligence and deep learning. The specific implementation solution is described below. A first audio signal is acquired, and a frequency domain feature of the first audio signal is extracted; and the frequency domain feature of the first audio signal is input into a voice activity detection model, and a voice presence detection result output by the voice activity detection model is obtained, where the voice activity detection model is configured to detect whether voice is present in the first audio signal.

Abstract: A method and apparatus for processing a signal. An implementation of the method includes: acquiring a reference signal of a to-be-tested voice, the reference signal being a signal output to a voice output device, where the voice output device outputs the to-be-tested voice after obtaining the reference signal; receiving, from a voice input device, an echo signal of the to-be-tested voice, the echo signal being a signal of the to-be-tested voice collected by the voice input device; performing signal preprocessing on the reference signal and the echo signal respectively; and inputting the processed reference signal and the processed echo signal into a pre-trained time delay estimation model, to obtain a time difference between the reference signal and the echo signal output by the time delay estimation model.