Voice Activity Detection Using Wavelet-Based Multiresolution Spectrum and Support Vector Machines and Audio Mixing Algorithm

Autor:	Yingxian Ye, Si-Dan Du, Wei Xue, Cheng-Zhi Fang
Rok vydání:	2006
Předmět:	Silence Support vector machine Noise Audio mixing Wavelet Voice activity detection Computer science Speech recognition Mel-frequency cepstrum Zero crossing Algorithm
Zdroj:	Computer Vision in Human-Computer Interaction ISBN: 9783540342021 ECCV Workshop on HCI
DOI:	10.1007/11754336_8
Popis:	This paper presents a Voice Activity Detection (VAD) algorithm and efficient speech mixing algorithm for a multimedia conference. The proposed VAD uses MFCC of multiresolution spectrum based on wavelets and two classical audio parameters as audio feature, and prejudges silence by detection of multi-gate zero cross ratio, and classify noise and voice by Support Vector Machines (SVM). New speech mixing algorithm used in Multipoint Control Unit (MCU) of conferences imposes short-time power of each audio stream as mixing weight vector, and is designed for parallel processing in program. Various experiments show, proposed VAD algorithm achieves overall better performance in all SNRs than VAD of G.729b and other VAD, output audio of new speech mixing algorithm has excellent hearing perceptibility, and its computational time delay are small enough to satisfy the needs of real-time transmission, and MCU computation is lower than that based on G.729b VAD.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::668988660e4b8841df80c6ac3088dff2 https://doi.org/10.1007/11754336_8 Zobrazit plný text záznamu