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...

Полное описание

Библиографические подробности
Главные авторы: Yanan Shang, Tianqi Fu
Формат: Статья
Язык:English
Опубликовано: Elsevier 2024-12-01
Серии:Intelligent Systems with Applications
Предметы:
Online-ссылка:http://www.sciencedirect.com/science/article/pii/S2667305324001108