Emotional Speech Analysis Based on Convolutional Neural Networks

Yi Chin Kao, Chung Ting Li, Tzu Chiang Tai, Jia Ching Wang

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

In recent studies, speech emotion recognition has been an intriguing and arduous area of research in human behavior analysis. The goal of this research area is to classify people's emotional states according to their speech tones. At present, the research area focuses on identifying the effectiveness of automatic classifiers of speech emotions to improve the classification efficiency in practical applications, e.g., for use in telecommunication services, identifying positive emotions (e.g., happy, surprise) and negative emotions (e.g., sad, angry, disgust, and fear), which can supply a large number of valid information for platform users and customers of telecommunication services.In this paper, the complex task of identifying positive and negative emotions in human voice data is investigated by using deep learning techniques. Five open emotion speech datasets are used to train multi-level models for positive and negative emotion recognition. The experimental results shows that our model can obtain good results for both positive and negative emotion speech data.

原文???core.languages.en_GB???
主出版物標題2021 9th International Conference on Orange Technology, ICOT 2021
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781665478427
DOIs
出版狀態已出版 - 2021
事件9th International Conference on Orange Technology, ICOT 2021 - Tainan, Taiwan
持續時間: 16 12月 202117 12月 2021

出版系列

名字2021 9th International Conference on Orange Technology, ICOT 2021

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???9th International Conference on Orange Technology, ICOT 2021
國家/地區Taiwan
城市Tainan
期間16/12/2117/12/21

指紋

深入研究「Emotional Speech Analysis Based on Convolutional Neural Networks」主題。共同形成了獨特的指紋。

引用此