Multimodal fusion: A study on speech-text emotion recognition with the integration of deep learning
Recognition of various human emotions holds significant value in numerous real-world scenarios. This paper focuses on the multimodal fusion of speech and text for emotion recognition. A 39-dimensional Mel-frequency cepstral coefficient (MFCC) was used as a feature for speech emotion. A 300-dimension...
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| Format: | Artikel |
| Sprache: | English |
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Elsevier
2024-12-01
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| Schriftenreihe: | Intelligent Systems with Applications |
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| Online Zugang: | http://www.sciencedirect.com/science/article/pii/S2667305324001108 |