TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Voice Frequency Synthesis using VAWGAN based Amplitude Scaling for Emotion Transformation |
| 영문제목(English Title) |
Voice Frequency Synthesis using VAWGAN based Amplitude Scaling for Emotion Transformation |
| 저자(Author) |
Hyochan Lee
Hyunhak Song
Sungyoon Cho
Kiwon Kwon
Sunghyun Park
Taeho Im
Hye-Jeong Kwon
Min-Jeong Kim
Ji-Won Baek
Kyungyong Chung
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| 원문수록처(Citation) |
VOL 16 NO. 02 PP. 0713 ~ 0725 (2022. 02) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Mostly, artificial intelligence does not show any definite change in emotions. For this reason, it is hard to demonstrate empathy in communication with humans. If frequency modification is applied to neutral emotions, or if a different emotional frequency is added to them, it is possible to develop artificial intelligence with emotions. This study proposes the emotion conversion using the Generative Adversarial Network (GAN) based voice frequency synthesis. The proposed method extracts a frequency from speech data of twenty-four actors and actresses. In other words, it extracts voice features of their different emotions, preserves linguistic features, and converts emotions only. After that, it generates a frequency in variational auto-encoding Wasserstein generative adversarial network (VAW-GAN) in order to make prosody and preserve linguistic information. That makes it possible to learn speech features in parallel. Finally, it corrects a frequency by employing Amplitude Scaling. With the use of the spectral conversion of logarithmic scale, it is converted into a frequency in consideration of human hearing features. Accordingly, the proposed technique provides the emotion conversion of speeches in order to express emotions in line with artificially generated voices or speeches.
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| 키워드(Keyword) |
Aid to Navigation
Maritime
Computer Vision
Object Detection
High-Speed
Processing
Emotion Transformation
Generative Adversarial Network
Voice Frequency
Synthesis
Voice Analysis
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