A novel speech/noise discrimination method for embedded ASR system

  • Authors:

  • Bian Wu;Xiaolin Ren;Chongqing Liu;Yaxin Zhang

  • Affiliations:

  • Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Motorola Labs China Research Center, Shanghai, China;Institute of Image Processing & Pattern Recognition, Shanghai Jiaotong University, Shanghai, China;Motorola Labs China Research Center, Shanghai, China

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2004

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Abstract

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.