Foundation Model Assisted Automatic Speech Emotion Recognition: Transcribing, Annotating, and Augmenting
Author:
Affiliation:
1. University of Southern California,Signal Analysis and Interpretation Laboratory,Los Angeles,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10445798/10445803/10448130.pdf?arnumber=10448130
Reference30 articles.
1. wav2vec 2.0: A framework for self-supervised learning of speech representations;Baevski;Advances in neural information processing systems,2020
2. wav2vec: Unsupervised Pre-Training for Speech Recognition
3. WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
4. Robust speech recognition via large-scale weak supervision;Radford,2022
5. IEMOCAP: interactive emotional dyadic motion capture database
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1. Speech Emotion Recognition Using Dual-Stream Representation and Cross-Attention Fusion;Electronics;2024-06-04
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