로그 우도 차이의 p-norm에 기반한 은닉 마르코프 파라미터 추정 알고리듬

Abstract

This paper proposes a discriminative training algorithm for estimating hidden Markov model (HMM) parameters. The proposed algorithm estimates the parameters by minimizing the p-norm of log-likelihood difference (PLD) between the utterance probability given the correct transcription and the most competitive transcription.