Mute test method and device

Abstract

The method detecting mute, avoiding excess linear prediction analysis to audio-frame only containing noise and having good detection rate and low complexity, includes: (1) pre-treating the first frame audio-frequency; (2) receiving next frame audio as current audio frame; (3) computing linear prediction weighting energy according to N-order linear prediction coefficient, in which N is a natural number; (4) predicting whether there is a voice signal according to the linear prediction weighing energy, if 'yes' which presents that the current frame is voice, going on next step, if 'no' which presents that the current frame is noise, turning to step (6); (5) linear predicting and analyzing current frame to obtain the N-order linear prediction coefficient of the frame itself to substitute the N-order linear prediction coefficient in original step (3); (6) judging whether current frame is the last one in frame series, if 'yes', ending, if 'no', turning to step (2).

Description

technical field [0001] The invention relates to a signal detection method, in particular to a method for detecting and recognizing speech and noise from a time sequence of audio frames. Background technique [0002] The transmission of the audio signal is basically carried out in the form of Fig. 1 . As shown in Figure 1, the audio signal must first be silently detected, the purpose of which is to detect or recognize speech and noise from the audio time series. The reason why it is necessary to use silence detection to distinguish speech and noise is because the general audio time series contains a lot of noise, sometimes even up to 50%. It would be wasteful to use the same codec method for noise and speech. Reasonable. After differentiating speech and noise, different codecs are performed on them, which not only saves the number of bits but also saves a certain amount of calculation. [0003] The silence detection method generally includes two stages, as shown in FIG. 2 ...

AI Technical Summary

Problems solved by technology

They have a common disadvantage: before silence detection, a linear prediction (LinearPrediction, LP) analysis must be performed on each frame of audio signal, and the time required for a linear prediction is O(N 2 ), where N is the order of the LP analysis

However, for frames containing only noise, LP analysis is not required, so it is unnecessary to perform LP analysis during silence detection, which is a waste

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