Verification of Normalized Confidence Measure Using n-Phone Based Statistics

  • Kim, Byoung-Don (Dept. of Electronics Eng., Chonnam National University) ;
  • Kim, Jin-Young (Dept. of Electronics Eng., Chonnam National University) ;
  • Na, Seung-You (Dept. of Electronics Eng., Chonnam National University) ;
  • Choi, Seung-Ho (Depart. of Multimedia Communications Eng., Dongshin University)
  • Published : 2005.03.01

Abstract

Confidence measure (CM) is used for the rejection of mis-recognized words in an automatic speech recognition (ASR) system. Rahim, Lee, Juang and Cho's confidence measure (RLJC-CM) is one of the widely-used CMs [1]. The RLJC-CM is calculated by averaging phone-level CMs. An extension of the RLJC-CM was achieved by Kim et al [2]. They devised the normalized CM (NCM), which is a statistically normalized version of the RLJC-CM by using the tri-phone based CM normalization. In this paper we verify the NCM by generalizing tri-phone to n-phone unit. To apply various units for the normalization, mono-phone, tri-phone, quin-phone and $\infty$-phone are tested. By the experiments in the domain of the isolated word recognition we show that tri-phone based normalization is sufficient enough to enhance the rejection performance of the ASR system. Also we explain the NCM in regard to two class pattern classification problems.

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