Multimodal Emotion Recognition from Raw Audio with Sinc-convolution
Multimodal Emotion Recognition from Raw Audio with Sinc-convolution
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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 (SER) is still a complex task for computers with average recall rates usually about 70% on the most realistic datasets. Most SER systems use hand-crafted features extracted from audio signal such as energy, zero crossing rate, spectral information, prosodic, mel frequency cepstral coefficient (MFCC), and so on. More recen...
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Multimodal Emotion Recognition from Raw Audio with Sinc-convolution
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TN_cdi_proquest_journals_2928716451
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2928716451
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E-ISSN
2331-8422
