Multi-Task Language Modeling for Improving Speech Recognition of Rare Words-Reference-Cited by-同舟云学术

Multi-Task Language Modeling for Improving Speech Recognition of Rare Words

Published:2021-12-13 Issue: Volume: Page:
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Container-title:2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)
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Author:

Yang Chao-Han Huck¹,Liu Linda¹,Gandhe Ankur¹,Gu Yile¹,Raju Anirudh¹,Filimonov Denis¹,Bulyko Ivan¹

Affiliation:

1. Amazon,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9687821/9687855/09688282.pdf?arnumber=9688282

Reference34 articles.

1. RNN Transducer Models for Spoken Language Understanding

2. Voice2series: Reprogramming acoustic models for time series classification;yang;Proceedings of the 38th International Conference on Machine Learning,2021

3. Adjunctemeritus distillation for semi-supervised language model adaptation;novotney;Proc INTERSPEECH 2021,0

4. PATE-AAE: Incorporating Adversarial Autoencoder into Private Aggregation of Teacher Ensembles for Spoken Command Classification

5. Leveraging Unpaired Text Data for Training End-To-End Speech-to-Intent Systems

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