Research on the Algorithm of Noisy-Robust Tibetan Speech Recognition Based on RBF

Author

Pan, Xiuqin ; Lu, Yong ; Cao, Yongcun ; Zhang, Hong ; Zhao, Yue ; Xu, Xiaona

Author_Institution

Sch. of Inf. Eng., Central Univ. for Nat., Beijing

fYear

2008

fDate

21-22 Dec. 2008

Firstpage

416

Lastpage

419

Abstract

Aiming at the problem of Tibetan speech recognition under the condition of resistance from noise, a kind of Tibetan speech recognition algorithm, combining RBF network with auditory feature was presented in this paper. The description for the Tibetan speech signals was carried out with Mel frequency cepstrum constant (MFCC), and the recognition classifier was designed based on RBF network with the property of supervised learning based on gradient descent. The simulation on the presented algorithm was run, and the results illustrates that the presented algorithm is valid.

Keywords

gradient methods; learning (artificial intelligence); radial basis function networks; speech recognition; Mel frequency cepstrum constant; RBF network; auditory feature; gradient descent methods; noisy-robust Tibetan speech recognition; recognition classifier; supervised learning; Frequency; Hidden Markov models; Information technology; Intelligent networks; Neural networks; Neurons; Radial basis function networks; Signal processing; Signal processing algorithms; Speech recognition; RBF; noisy-robust; speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Technology Application Workshops, 2008. IITAW '08. International Symposium on

Conference_Location

Shanghai

Print_ISBN

978-0-7695-3505-0

Type

conf

DOI

10.1109/IITA.Workshops.2008.261

Filename

4731966