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...
Auteurs principaux: | , |
---|---|
Format: | Article |
Langue: | English |
Publié: |
Elsevier
2024-12-01
|
Collection: | Intelligent Systems with Applications |
Sujets: | |
Accès en ligne: | http://www.sciencedirect.com/science/article/pii/S2667305324001108 |