Papers

Efficient deep neural networks for speech synthesis using bottleneck features

International Conference
2016~2020
작성자
한혜원
작성일
2016-12-01 16:29
조회
1367
Authors : Young-Sun Joo, Won-Suk Jun, Hong-Goo Kang

Year : 2016

Publisher / Conference : APSIPA

This paper proposes a cascading deep neural network (DNN) structure for speech synthesis system that consists of text-to-bottleneck (TTB) and bottleneck-to-speech (BTS) models. Unlike conventional single structure that requires a large database to find complicated mapping rules between linguistic and acoustic features, the proposed structure is very effective even if the available training database is inadequate. The bottle-neck feature utilized in the proposed approach represents the characteristics of linguistic features and its average acoustic features of several speakers. Therefore, it is more efficient to learn a mapping rule between bottleneck and acoustic features than to learn directly a mapping rule between linguistic and acoustic features. Experimental results show that the learning capability of the proposed structure is much higher than that of the conventional structures. Objective and subjective listening test results also verify the superiority of the proposed structure.
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295 Domestic Conference 임정운, 김지현, 강홍구 "메타러닝을 이용한 SAR 영상 자동표적 인식" in 한국항공우주학회 2020 춘계학술대회, pp.353-354, 2020
294 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
293 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
292 International Journal Soo-Whan Chung, Joon Son Chung, Hong Goo Kang "Perfect Match: Self-Supervised Embeddings for Cross-Modal Retrieval" in IEEE Journal of Selected Topics in Signal Processing, vol.14, issue 3, 2020
291 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
290 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
289 International Conference Min-Jae Hwang, Hong-Goo Kang "Parameter enhancement for MELP speech codec in noisy communication environment" in INTERSPEECH, 2019
288 Domestic Journal 오상신, 엄세연, 장인선, 안충현, 강홍구 "k-평균 알고리즘을 활용한 음성의 대표 감정 스타일 결정 방법" in 한국음향학회지, vol.38, 제 5호, pp.614-620, 2019
287 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
286 International Conference Keulbit Kim, Jinkyu Lee, Jan Skoglund, Hong-Goo Kang "Model Order Selection for Wind Noise Reduction in Non-negative Matrix Factorization" in ITC-CSCC, 2019