Emotion Detection via Voice and Speech Recognition

Emotion Detection via Voice and Speech Recognition

Rohit Rastogi, Tushar Anand, Shubham Kumar Sharma, Sarthak Panwar
Copyright: © 2023 |Pages: 24
DOI: 10.4018/IJCBPL.333473
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Abstract

Emotion detection from voice signals is needed for human-computer interaction (HCI), which is a difficult challenge. In the literature on speech emotion recognition, various well known speech analysis and classification methods have been used to extract emotions from signals. Deep learning strategies have recently been proposed as a workable alternative to conventional methods and discussed. Several recent studies have employed these methods to identify speech-based emotions. The review examines the databases used, the emotions collected, and the contributions to speech emotion recognition. The Speech Emotion Recognition Project was created by the research team. It recognizes human speech emotions. The research team developed the project using Python 3.6. RAVDEESS dataset was also used since it contained eight distinct emotions expressed by all speakers. The RAVDESS dataset, Python programming languages, and Pycharm as an IDE were all used by the author team.
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Ethical Committee And Funding

The experiments don't include any human-related experiments and so no ethical constraints have been violated. Though the subjects performing the study were humans and air quality directly affects them but the study doesn’t violate any health-related measures. The Project is not funded by any agency.

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