JSAI2022

Presentation information

General Session

General Session » GS-2 Machine learning

[1A4-GS-2] Machine learning: recommendation / feature analysis

Tue. Jun 14, 2022 2:20 PM - 4:00 PM Room A (Main Hall)

座長:竹岡 邦紘(NEC)[現地]

3:40 PM - 4:00 PM

[1A4-GS-2-05] A Study of Emotion Classification Using Neural Network with Voice Data

〇Masashi Takaku1, Shoichi Urano1 (1. Meiji University)

Keywords:Voice Recognition, Neural Network, Machine Learning, Emotion Classification, Cepstrum Analysis

The purpose of this study is to create a highly accurate emotion classification model for voice by analyzing the entire voice waveform and extracting the features of voice data for each emotion. In this paper, we created an emotion classification model using neural network for the purpose of more accurate emotion classification of voice data. We then evaluated the model and compared its accuracy with that of a model created using decision trees.

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