Abstract— This paper presents a high performance embedded non-specific, medium vocabulary Chinese-English bilingual speech recognition system using the continuous density hidden Markov model and a two-pass search strategy based on a 16-bit fixed-point digital signal processing (DSP). This system selecting MFCC parameters as recognition feature. Improve the system real-time through a dedicated hardware circuit design. We extract specialized hardware co-processing circuit characterized by structural features through abstracting algorithm critical path that speedy computation concerns much in speech recognition, so as to greatly enhance the overall performance by little chip costs. The experimental result suggested that the identification rate is 97.6% when entries sum is 600. The characteristic storage space was reduced 31%, and the real-time rate of two stage identification is 0.7.

Index Terms— speech recognition, system on chip, dsp, model selection.

Shunli Ding is with Tsinghua National Laboratory for Information Science and Technology, Beijing, China (e-mail: lntaishan@126.com).
Hong Cao is with HELIOS-ADSP Technology Co.Ltd, Beijing, China (e-mail: ted@helios-adsp.com.cn).
Jia Liu is with EE Department of Tsinghua University, Beijing, China (e-maill:liuj@tsinghua.edu.cn).

Cite: Shunli Ding, Hong Cao, and Jia Liu, " The Implementation of Chinese and English Bilingual Speech Recognition System-on-Chip," International Journal of e-Education, e-Business, e-Management and e-Learning vol. 3, no. 6, pp. 432-435, 2013.