Speech Recognition in Aphasiac Rehabilitation Based on Wavelet

Author

Du Jingyi ; Li Ani ; Wang Lu

Author_Institution

Sch. of Electr. & Control Eng., Xi´an Univ. of Sci. & Technol., Xi´an, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

3

Abstract

The abstract of real voice of the aphasiacs is of great importance in the rehabilitation system. In this paper a new method of using wavelet for rehabilitation system was raised, it also improves the wavelet decomposition by refining its high frequency part in order to improve the SNR of voices. Simulation was given by using the combination of advanced wavelet decomposition and soft thresholding. The experiment results showed that this new method is efficient in enhancing the SNR and reserving the energy of effective signals. It supplements the deficiency of soft thresholding and aquires good results without noises. It has practical significance for auditory rehabilitation system for aphasiac patients.

Keywords

patient rehabilitation; speech recognition; wavelet transforms; aphasiac rehabilitation; auditory rehabilitation system; soft thresholding; speech recognition; wavelet decomposition; Frequency; Gaussian noise; Low-frequency noise; Noise reduction; Signal analysis; Signal processing; Speech recognition; Wavelet coefficients; Wavelet domain; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5366934

Filename

5366934