Enhancing Speech Emotion Recognition for Real-World Applications via ASR Integration
Author:
Affiliation:
1. University of Edinburgh,Centre for Speech Technology Research,Edinburgh,UK
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10388069/10388071/10388136.pdf?arnumber=10388136
Reference41 articles.
1. The INTERSPEECH 2009 emotion challenge
2. The INTERSPEECH 2013 computational paralinguistics challenge: social signals, conflict, emotion, autism
3. GMM Supervector Based SVM with Spectral Features for Speech Emotion Recognition
4. Improved End-to-End Speech Emotion Recognition Using Self Attention Mechanism and Multitask Learning
5. Recognizing emotions in spoken dialogue with hierarchically fused acoustic and lexical features
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