Mute detection method based on speech characteristic to jude

Abstract

The invention discloses a voice characteristic identification-based silence detecting method, firstly extracting multi-threshold overzero rate of an audio data frame; pre-identify silence by weighting the multi-threshold overzero rate to identify obvious silence; extracting composite characteristic of an audio data frame, where the composite characteristic comprises overzero rate, short-time energy value, and variable resolution frequency spectrum-based Mel scale revere spectrum coefficient; using dichotomy support vector machine to identify the composite character of the audio frequency, one class normal voice and the other class silence. And the invention can raise success rate of silence detection and can identify some special voices, able to be widely applied to network voice talking, especially voice chatting and video meeting.

Description

1. Technical field

[0001] The invention relates to an audio processing method, in particular to a method for detecting silence based on speech feature discrimination for Internet voice calls. 2. Background technology

[0002] In the process of human speaking, its voice can be divided into two parts: silence and voice, and 60% of the time is silence on average. And when many people are talking, basically only one person speaks at each moment, while the others are silent. Silence and noise (including airflow noise) introduced by voice collection equipment are transmitted in the network like voice data, causing voice quality to degrade. Using the mute suppression technology, the mute part can be eliminated, which can save more than 50% of the transmission bandwidth and reduce network congestion.

[0003] Existing silence detection methods include extracting audio signal eigenvalues ​​and comparing them with preset thresholds to determine silence. The parameters used in tradit...

Images