Proceedings of the KSPS conference (대한음성학회:학술대회논문집)

The Korean Society Of Phonetic Sciences And Speech Technology (대한음성학회)
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Robust Speech Recognition Using Real-Time High Order Statistics Normalization and Smoothing Filter

실시간 고차통계 정규화와 Smoothing 필터를 이용한 강인한 음성인식

  • Jeong, Ju-Hyun (Dept. of Electronics Engineering, Pusan National University) ;
  • Song, Hwa-Jeon (Dept. of Electronics Engineering, Pusan National University) ;
  • Kim, Hyung-Soon (Dept. of Electronics Engineering, Pusan National University)
  • Published : 2005.04.27
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Abstract

The performance of speech recognition is degraded by the mismatch between training and test environments. Many methods have been presented to compensate for additive noise and channel effect in the cepstral domain, and Cepstral Mean Subtraction (CMS) is the representative method among them. Recently, high order cepstral moment normalization method has introduced to improve recognition accuracy. In this paper, we apply high order moment normalization method and smoothing filter for real-time processing. In experiments using Aurora2 DB, we obtained error rate reduction of 49.7% with the proposed algorithm in comparison with baseline system.

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