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题名: A speaker-independent continuous speech recognition system using biomimetic pattern recognition
作者: Wang SJ (Wang Shoujue);  Qin H (Qin Hong)
发表日期: 2006
摘要: In speaker-independent speech recognition, the disadvantage of the most diffused technology (HMMs, or Hidden Markov models) is not only the need of many more training samples, but also long train time requirement. This paper describes the use of Biomimetic pattern recognition (BPR) in recognizing some mandarin continuous speech in a speaker-independent manner. A speech database was developed for the course of study. The vocabulary of the database consists of 15 Chinese dish's names, the length of each name is 4 Chinese words. Neural networks (NNs) based on Multi-weight neuron (MWN) model are used to train and recognize the speech sounds. The number of MWN was investigated to achieve the optimal performance of the NNs-based BPR. This system, which is based on BPR and can carry out real time recognition reaches a recognition rate of 98.14% for the first option and 99.81% for the first two options to the persons from different provinces of China speaking common Chinese speech. Experiments were also carried on to evaluate Continuous density hidden Markov models (CDHMM), Dynamic time warping (DTW) and BPR for speech recognition. The Experiment results show that BPR outperforms CDHMM and DTW especially in the cases of samples of a finite size.
KOS主题词: Speech perception
刊名: CHINESE JOURNAL OF ELECTRONICS
专题: 中国科学院半导体研究所(2009年前)_期刊论文

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推荐引用方式:
Wang SJ (Wang Shoujue); Qin H (Qin Hong) .A speaker-independent continuous speech recognition system using biomimetic pattern recognition ,CHINESE JOURNAL OF ELECTRONICS,2006,15(3):460-462
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