Voice activity detection method and equipment based on time domain and frequency domain

Abstract

The invention discloses a voice activity detection method and equipment based on a time domain and a frequency domain. The method comprises the steps that noise energy of voice signals is estimated; white noise is added into the input voice signals; the voice signals after the white noise is added are processed in a framing mode; a short-time energy value of each frame is determined; a harmonic wave product spectrum value of each frame is determined; for each frame, whether the frame is a voice frame is determined according to the short-time energy value and the harmonic wave product spectrum value of the frame, and voice segments contained in the voice signals are obtained. According to the voice activity detection method and equipment, a time domain analysis method and a frequency domain analysis method are combined, the adaptability is high for the actual condition, performance is good under the circumstances that the background noise is human voice and the signal to noise ratio is low, the method is easy and ingenious to realize, and the equipment can be embedded into various voice systems easily.

Description

technical field [0001] The present invention relates to the field of voice activity detection, in particular to a voice activity detection method and device based on time domain and frequency domain. Background technique [0002] Voice Activity Detection (Voice Activity Detection, VAD) is a speech processing technology for detecting the presence of a speech signal. Speech activity detection technology is mainly used for speech recognition, speech coding, etc. It can distinguish silence and speech fragments, paving the way for further processing of speech signals. The voice activity detection module is also an integral part of many voice communication systems, such as audio conferencing, voice recognition, echo cancellation, IP telephony, etc. For the speech recognition system, the accuracy of the speech activity detection module will greatly affect the subsequent work of feature extraction, model building and judgment. Therefore, it is particularly important to provide effi...

AI Technical Summary

Problems solved by technology

However, in actual use, there are often situations where the signal-to-noise ratio is low and the background noise is also human voice. At this time, it is difficult to obtain sufficiently accurate results using traditional methods.

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