Paper
19 July 2013 The short-time spectrum analysis of real-time sampling speech with DSP TMS320VC5416 chip
Qinru Fan, Wen-hua Ren
Author Affiliations +
Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88783J (2013) https://doi.org/10.1117/12.2030641
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China
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.
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Qinru Fan and Wen-hua Ren "The short-time spectrum analysis of real-time sampling speech with DSP TMS320VC5416 chip", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88783J (19 July 2013); https://doi.org/10.1117/12.2030641
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KEYWORDS
Digital signal processing

Detection and tracking algorithms

Spectrum analysis

Speech recognition

Computer simulations

Fourier transforms

Signal processing

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