Exploring Teacher-Student Learning Approach for Multi-Lingual Speech-to-Intent Classification-Reference-Cited by-同舟云学术

Exploring Teacher-Student Learning Approach for Multi-Lingual Speech-to-Intent Classification

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

Sharma Bidisha¹,Madhavi Maulik¹,Zhou Xuehao¹,Li Haizhou¹

Affiliation:

1. National University of Singapore,Department of Electrical and Computer Engineering,Singapore

Funder

Agency for Science, Technology and Research (A*STAR)

Science and Engineering Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9687821/9687855/09688041.pdf?arnumber=9688041

Reference35 articles.

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2. Efficiently trainable text-to-speech sys-tem based on deep convolutional networks with guided attention;tachibana;International Conference on Acoustics Speech and Signal Processing (ICASSP),2018

3. Signal estimation from modified short-time Fourier transform

4. End-to-End Code-Switching TTS with Cross-Lingual Language Model

5. Visualizing data using t-SNE;maaten;Journal of Machine Learning Research,2008

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1. Probability-Aware Word-Confusion-Network-To-Text Alignment Approach for Intent Classification;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14

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