Fusing ASR Outputs in Joint Training for Speech Emotion Recognition-Reference-Cited by-同舟云学术

Fusing ASR Outputs in Joint Training for Speech Emotion Recognition

Published:2022-05-23 Issue: Volume: Page:
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Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Li Yuanchao¹,Bell Peter¹,Lai Catherine¹

Affiliation:

1. University of Edinburgh,Centre for Speech Technology Research,Scotland, UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746289.pdf?arnumber=9746289

Reference21 articles.

1. ASR-based Features for Emotion Recognition: A Transfer Learning Approach

2. End-to-End Speech Emotion Recognition Combined with Acoustic-to-Word ASR Model

3. Improved End-to-End Speech Emotion Recognition Using Self Attention Mechanism and Multitask Learning

4. Wav2vec 2.0: A framework for self-supervised learning of speech representations;baevski;Advances in neural information processing systems,2020

5. Prosodic characteristics of emotional speech: Measurements of fundamental frequency movements;paeschke;ISCA Tutorial and Research Workshop ITRW on Speech and Emotion,2000

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