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Proceedings Paper

The short-time spectrum analysis of real-time sampling speech with DSP TMS320VC5416 chip
Author(s): Qinru Fan; Wen-hua Ren
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Paper Abstract

For automatic speech recognition (ASR), the research centers mainly on algorithm of improving robust, researchers put less emphasis on realization and application of better speech algorithm. Real-time proceeding of speech recognition directly influence on its application, so real-time proceeding of speech recognition is as important as study of algorithm. Speech transform domain method is a necessary technique of speech recognition, so real-time analysis of transform domain method is necessary. In transform domain methods, the short-time spectrum analysis is simple and easy to realize, especially the short-time FFT algorithm is applied to the short-time spectrum analysis. FFT algorithm reduces multiplications greatly. For the purpose, this paper presents short-time spectrum analysis of real-time sampling speech based on FFT algorithm. We use DSP TMS320VC5416 chip and speech codec ASIC TLV320AIC23 as hardware, the real-time speech signal is acquired by ASIC TLV320AIC23. When working frequency of TMS320VC5416 is set 160 MHz and sampling frequency is 44.1 kHz, the short-time FFT is radix-2 DIF-FFT algorithm and the length of short-time window is 128, the simulation waves and data show that the short-time FFT algorithm analysis based on TMS320VC5416 chip can meet real-time of system. For estimation of proceeding error, we make a calculation of radix- 2 DIT-IFFT. Comparing the result of DIT-IFFT and sampling speech data, error is less than 10-3.

Paper Details

Date Published: 19 July 2013
PDF: 6 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88783J (19 July 2013); doi: 10.1117/12.2030641
Show Author Affiliations
Qinru Fan, Zhejiang Univ. Ningbo Institute of Technology (China)
Wen-hua Ren, Zhejiang Police College (China)

Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

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