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...

Повний опис

Бібліографічні деталі
Автори: Yanan Shang, Tianqi Fu
Формат: Стаття
Мова:English
Опубліковано: Elsevier 2024-12-01
Серія:Intelligent Systems with Applications
Предмети:
Онлайн доступ:http://www.sciencedirect.com/science/article/pii/S2667305324001108