MAP-based perceptual modeling for noisy speech recognition

Yung Ji Sher*, Yeou Jiunn Chen, Yu Hsien Chiu, Kao Chi Chung, C. H. Wu


研究成果: 雜誌貢獻期刊論文同行評審

3 引文 斯高帕斯(Scopus)


This study presents a maximum a posteriori (MAP) based perceptual modeling approach to deal with the issue of recognition degradation in noisy environment. In this approach, MAP-based noise detection is first applied to identify the noise segment in an utterance. Subtractive-type enhancement algorithm with masking properties of the human auditory system is then used to reduce the noise effect. Finally, MAP-based incremental noise model adaptation is developed to overcome the model inconsistencies between training and testing environments. For performance evaluation of the proposed approach, a Mandarin keyword recognition system was constructed. The experimental results show that the proposed approach achieves a better recognition rate compared to the audible noise suppression (ANS) and parallel model combination (PMC) methods.

頁(從 - 到)999-1013
期刊Journal of Information Science and Engineering
出版狀態已發佈 - 2006 9月

ASJC Scopus subject areas

  • 軟體
  • 人機介面
  • 硬體和架構
  • 圖書館與資訊科學
  • 計算機理論與數學


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