Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition
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arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2019
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| _version_ | 1866910911176900608 |
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| author | Tripathi, Suraj Kumar, Abhay Ramesh, Abhiram Singh, Chirag Yenigalla, Promod |
| author_facet | Tripathi, Suraj Kumar, Abhay Ramesh, Abhiram Singh, Chirag Yenigalla, Promod |
| contents | This paper proposes a Residual Convolutional Neural Network (ResNet) based on speech features and trained under Focal Loss to recognize emotion in speech. Speech features such as Spectrogram and Mel-frequency Cepstral Coefficients (MFCCs) have shown the ability to characterize emotion better than just plain text. Further Focal Loss, first used in One-Stage Object Detectors, has shown the ability to focus the training process more towards hard-examples and down-weight the loss assigned to well-classified examples, thus preventing the model from being overwhelmed by easily classifiable examples. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_1906_05682 |
| institution | arXiv |
| publishDate | 2019 |
| record_format | arxiv |
| spellingShingle | Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition Tripathi, Suraj Kumar, Abhay Ramesh, Abhiram Singh, Chirag Yenigalla, Promod Audio and Speech Processing Artificial Intelligence Machine Learning Sound This paper proposes a Residual Convolutional Neural Network (ResNet) based on speech features and trained under Focal Loss to recognize emotion in speech. Speech features such as Spectrogram and Mel-frequency Cepstral Coefficients (MFCCs) have shown the ability to characterize emotion better than just plain text. Further Focal Loss, first used in One-Stage Object Detectors, has shown the ability to focus the training process more towards hard-examples and down-weight the loss assigned to well-classified examples, thus preventing the model from being overwhelmed by easily classifiable examples. |
| title | Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition |
| topic | Audio and Speech Processing Artificial Intelligence Machine Learning Sound |
| url | https://arxiv.org/abs/1906.05682 |