Papers

An Effective Style Token Weight Control Technique for End-to-End Emotional Speech Synthesis

International Journal
2016~2020
작성자
이진영
작성일
2019-09-01 22:16
조회
3068
Authors : Ohsung Kwon, Inseon Jang, ChungHyun Ahn, Hong-Goo Kang

Year : 2019

Publisher / Conference : IEEE Signal Processing Letters

Volume : 26, issue 9

Page : 1383-1387

In this letter, we propose a high-quality emotional speech synthesis system, using emotional vector space, i.e., the weighted sum of global style tokens (GSTs). Our previous research verified the feasibility of GST-based emotional speech synthesis in an end-to-end text-to-speech synthesis framework. However, selecting appropriate reference audio (RA) signals to extract emotion embedding vectors to the specific types of target emotions remains problematic. To ameliorate the selection problem, we propose an effective way of generating emotion embedding vectors by utilizing the trained GSTs. By assuming that the trained GSTs represent an emotional vector space, we first investigate the distribution of all the training samples depending on the type of each emotion. We then regard the centroid of the distribution as an emotion-specific weighting value, which effectively controls the expressiveness of synthesized speech, even without using the RA for guidance, as it did before. Finally, we confirm that the proposed controlled weight-based method is superior to the conventional emotion label-based methods in terms of perceptual quality and emotion classification accuracy.
전체 369
117 International Conference Hyewon Han, Soo-Whan Chung, Hong-Goo Kang "MIRNet: Learning multiple identities representations in overlapped speech" in INTERSPEECH, 2020
116 International Conference Yoohwan Kwon, Soo-Whan Chung, Hong-Goo Kang "Intra-Class Variation Reduction of Speaker Representation in Disentanglement Framework" in INTERSPEECH, 2020
115 International Conference Minh-Tri Ho, Jinyoung Lee, Bong-Ki Lee, Dong Hoon Yi, Hong-Goo Kang "A Cross-channel Attention-based Wave-U-Net for Multi-channel Speech Enhancement" in INTERSPEECH, 2020
114 International Journal Young-Sun Joo, Hanbin Bae, Young-Ik Kim, Hoon-Young Cho, Hong-Goo Kang "Effective Emotion Transplantation in an End-to-End Text-to-Speech System" in IEEE Access, vol.8, pp.161713-161719, 2020
113 International Conference Seyun Um, Sangshin Oh, Kyungguen Byun, Inseon Jang, ChungHyun Ahn, Hong-Goo Kang "Emotional Speech Synthesis with Rich and Granularized Control" in ICASSP, 2020
112 International Conference Min-Jae Hwang, Eunwoo Song, Ryuichi Yamamoto, Frank Soong, Hong-Goo Kang "Improving LPCNet-based Text-to-Speech with Linear Prediction-structured Mixture Density Network" in ICASSP, 2020
111 International Conference Hyeonjoo Kang, Young-Sun Joo, Inseon Jang, Chunghyun Ahn, Hong-Goo Kang "A Study on Acoustic Parameter Selection Strategies to Improve Deep Learning-Based Speech Synthesis" in APSIPA, 2019
110 International Journal Ohsung Kwon, Inseon Jang, ChungHyun Ahn, Hong-Goo Kang "An Effective Style Token Weight Control Technique for End-to-End Emotional Speech Synthesis" in IEEE Signal Processing Letters, vol.26, issue 9, pp.1383-1387, 2019
109 International Conference Min-Jae Hwang, Hong-Goo Kang "Parameter enhancement for MELP speech codec in noisy communication environment" in INTERSPEECH, 2019
108 International Journal Jinkyu Lee, Hong-Goo Kang "A Joint Learning Algorithm for Complex-Valued T-F Masks in Deep Learning-Based Single-Channel Speech Enhancement Systems" in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.27, issue 6, pp.1098-1108, 2019