Intelligent speech recognition system based on self-adaption psychoacoustic model
XIONG Xiao-yan
CHEN Xu
HUANG Can-ying
CHEN Yan
Abstract：Aiming at such noise speech processing problems as environmental noise and channel distortion, an intelligent speech recognition system based on adaptive psychoacoustic system was proposed, and an auditory model was established. In the proposed model, the psychoacoustics and otoacoustic emission ( OAE) were integrated into an automatic speech recognition ( ASR ) system. With the AURORA2 database, the experiments were performed under both clean and multiple training conditions, respectively. The results show that the proposed feature extraction method can significantly improve the word recognition rate, is superior to those of Mel-frequency cepstral coefficients ( MFCCs) , forward masking ( FM) , lateral inhibition ( LI ) and cepstral mean & variance normalization ( CMVN ) algorithms, and can effectively enhance the performance of intelligent speech recognition system.
Keywords：Mel-frequency cepstral coefficient ( MFCC )otoacoustic emission ( OAE )self-adaptionpsychoacoustic filterautomatic speech recognition ( ASR )AURORA2 databaseforward masking ( FM)lateral inhibition ( LI)
Publication Date：2017-11-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 675-679 )