Sentiment-Aware Automatic Speech Recognition pre-training for enhanced Speech Emotion Recognition

• URL: http://arxiv.org/abs/2201.11826v1
• Date: Thu, 27 Jan 2022 22:20:28 GMT
• Title: Sentiment-Aware Automatic Speech Recognition pre-training for enhanced Speech Emotion Recognition
• Authors: Ayoub Ghriss, Bo Yang, Viktor Rozgic, Elizabeth Shriberg, Chao Wang
• Abstract summary: We propose a novel multi-task pre-training method for Speech Emotion Recognition (SER) We pre-train SER model simultaneously on Automatic Speech Recognition (ASR) and sentiment classification tasks. We generate targets for the sentiment classification using text-to-sentiment model trained on publicly available data.
• Score: 11.760166084942908
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a novel multi-task pre-training method for Speech Emotion Recognition (SER). We pre-train SER model simultaneously on Automatic Speech Recognition (ASR) and sentiment classification tasks to make the acoustic ASR model more ``emotion aware''. We generate targets for the sentiment classification using text-to-sentiment model trained on publicly available data. Finally, we fine-tune the acoustic ASR on emotion annotated speech data. We evaluated the proposed approach on the MSP-Podcast dataset, where we achieved the best reported concordance correlation coefficient (CCC) of 0.41 for valence prediction.

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