LFMMI-based acoustic modeling by using external knowledge

JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA(2019)

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摘要
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.
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关键词
Speech recognition,Acoustic model,LF-MMI (Lattice Free Maximum Mutual Information),Phoneme-based language
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