tailieunhanh - Báo cáo hóa học: " A Novel Speech/Noise Discrimination Method for Embedded ASR System"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: A Novel Speech/Noise Discrimination Method for Embedded ASR System | EURASIP Journal on Applied Signal Processing 2004 11 1721-1726 2004 Hindawi Publishing Corporation A Novel Speech Noise Discrimination Method for Embedded ASR System Bian Wu Institute of Image Processing Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China Email wu_bian@ Xiaolin Ren Motorola Labs China Research Center Shanghai 200041 China Email Chongqing Liu Institute of Image Processing Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China Email liuchqing@ Yaxin Zhang Motorola Labs China Research Center Shanghai 200041 China Email Received 30 October 2003 Revised 8 February 2004 Recommended for Publication by Sadaoki Furui The problem of speech noise discrimination has become increasingly important as the automatic speech recognition ASR system is applied in the real world. Robustness and simplicity are two challenges to the speech noise discrimination method for an embedded system. The energy-based feature is the most suitable and applicable feature for speech noise discrimination for embedded ASR system because of effectiveness and simplicity. A new method based on a noise model is proposed to discriminate speech signals from noise signals. The noise model is initialized and then updated according to the signal energy. The experiment shows the effectiveness and robustness of the new method in noisy environments. Keywords and phrases noise robustness speech noise discrimination automatic speech recognition. 1. INTRODUCTION The problem of speech noise discrimination has become increasingly important as the automatic speech recognition ASR system is applied in the real world. Robustness and simplicity are the basic requirements of a speech noise discrimination method for an embedded ASR system. The discrimination method should be robust in various noisy environments at various SNRs. Low complexity is another challenge because of the requirement of real-time and .

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