LFMMI-based acoustic modeling by using external knowledge

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초록

This paper proposes LF-MMI (Lattice Free Maximum Mutual Information)-based acoustic modeling using external knowledge for speech recognition. Note that an external knowledge refers to text data other than training data used in acoustic model. LF-MMI, objective function for optimization of training DNN (Deep Neural Network), has high performances in discriminative training. In LF-MMI, a phoneme probability as prior probability is used for predicting posterior probability of the DNN-based acoustic model. We propose using external knowledges for training the prior probability model to improve acoustic model based on DNN. It is measured to relative improvement 14 % as compared with the conventional LF-MMI-based model. © 2019 Acoustical Society of Korea. All rights reserved.

키워드

Speech recognitionAcoustic modelLF-MMI (Lattice Free Maximum Mutual Information)Phoneme- based language음성인식음향모델lattice 없는 상호 정보 최대화음소 기반 언어 모델
제목
LFMMI-based acoustic modeling by using external knowledge
저자
Park, HosungKim, Ji Hwan
DOI
10.7776/ASK.2019.38.5.607
발행일
2019
유형
Article
저널명
한국음향학회지
38
5
페이지
607 ~ 613