International Journal of Mathematical Sciences and Computing (IJMSC)
IJMSC Vol. 7, No. 1, 8 Feb. 2021
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A System to Predict Emotion from Bengali Speech
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Author(s)
Prashengit Dhar
1,*
Sunanda Guha
2
Index Terms
Speech recognition, Bengali speech, MFCC, LPC, XgBoost
Abstract
Predicting human emotion from speech is now important research topic. One’s mental state can be understood by emotion. The proposed research work is emotion recognition from human speech. Proposed system plays significant role in recognizing emotion while someone is talking. It has a great use for smart home environment. One can understand the emotion of other who is in home or may be in other place. University, service center or hospital can get a valuable decision support system with this emotion prediction system. Features like-MFCC (Mel-Frequency Cepstral Coefficients) and LPC are extracted from audio sample signal. Audios are collected by recording speeches. A test also applied by combining self-collected dataset and popular Ravdees dataset. Self-collected dataset is named as ABEG. MFCC and LPC features are used in this study to train and test for predicting emotion. This study is made on angry, happy and neutral emotion classes. Different machine learning algorithms are applied here and result is compared with each other. Logistic regression performs well as compared to other ML algorithm.
Cite This Paper
Prashengit Dhar, Sunanda Guha," A System to Predict Emotion from Bengali Speech ", International Journal of Mathematical Sciences and Computing(IJMSC), Vol.7, No.1, pp. 26-35, 2021. DOI: 10.5815/ijmsc.2021.01.04
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