Language modeling for spontaneous speech recognition based on disfluency labeling and generation of disfluent text
Author:
Affiliation:
1. Toyohashi University of Technology
2. National Institute of Technology, Anan College
3. Tokushima University
4. NTT Corporation,Japan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10317071/10317095/10317137.pdf?arnumber=10317137
Reference29 articles.
1. Towards Better Decoding and Language Model Integration in Sequence to Sequence Models
2. Sequence to sequence learning with neural networks;sutskever;Proc NIPS,2014
3. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding;devlin;Proc NAACL-HLT,2019
4. An Analysis of Incorporating an External Language Model into a Sequence-to-Sequence Model
5. End-to-End Spontaneous Speech Recognition Using Disfluency Labeling
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