Recognizing Speech Emotion Based on Acoustic Features Using Machine Learning

Abu Saleh Nasim, Rakibul Hassan Chowdory,Ashim Dey,Annesha Das

2021 International Conference on Advanced Computer Science and Information Systems (ICACSIS)（2021）

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Abstract

Detecting emotion from speech can be helpful to understand the state of individual's mind. Accurately classifying emotion from speech is a very challenging job. In this work, we combined two datasets- Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) and Toronto Emotional Speech Set (TESS) to diversify the speech dataset. The resulting dataset contains 4048 audio files. Seven ke...

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Key words

Mel-Frequency Cepstral Coefficient (MFCC),Chroma,Mel Spectrogram,RAVDESS dataset,TESS dataset,Speech emotion recognition (SER),Human-computer interaction (HCI)

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