Bimodal Speech Emotion Recognition Using Pre-Trained Language Models
Bimodal Speech Emotion Recognition Using Pre-Trained Language Models
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Ithaca: Cornell University Library, arXiv.org
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English
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Ithaca: Cornell University Library, arXiv.org
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Speech emotion recognition is a challenging task and an important step towards more natural human-machine interaction. We show that pre-trained language models can be fine-tuned for text emotion recognition, achieving an accuracy of 69.5% on Task 4A of SemEval 2017, improving upon the previous state of the art by over 3% absolute. We combine these...
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Bimodal Speech Emotion Recognition Using Pre-Trained Language Models
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TN_cdi_proquest_journals_2322260067
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2322260067
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2331-8422
