Papers

Efficient deep neural networks for speech synthesis using bottleneck features

International Conference
2016~2020
작성자
한혜원
작성일
2016-12-01 16:29
조회
1421
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.
전체 355
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17 International Conference Young-Sun Joo, Won-Suk Jun, Hong-Goo Kang "Efficient deep neural networks for speech synthesis using bottleneck features" in APSIPA, 2016
16 Domestic Journal 문현기, 박영철, 황영수 "위상 일치와 가변 지수 감쇠 가중치 부여 방법이 적용된 가상 저음 시스템" in 방송공학회논문지, vol.21, 제 6호, pp.889-898, 2016
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14 International Conference Haemin Yang, Kyungguen Byun, Youngsu Kwak, Hong-Goo Kang "Parametric-based non-intrusive speech quality assessment by deep neural network" in 21th International Conference on Digital Signal Processing (DSP), 2016
13 International Conference Jin-Seob Kim, Young-Sun Joo, Inseon Jang, ChungHyun Ahn, Jeongil Seo, Hong-Goo Kang "A pitch-synchronous speech analysis and synthesis method for DNN-SPSS system" in 21th International Conference on Digital Signal Processing (DSP), 2016
12 International Conference Eunwoo Song, Frank K. Soong, Hong-Goo Kang "Improved Time-Frequency Trajectory Excitation Vocoder for DNN-Based Speech Synthesis" in INTERSPEECH, 2016
11 Domestic Conference Hyeonjoo Kang, Young-sun Joo, Wonsuk Jun, Hong-goo Kang "다층신경망 기반 다중 화자 음성변환 시스템" in 한국음향학회 제 33회 음성통신 및 신호처리 학술대회, 2016
10 International Conference Eunwoo Song, Hong-Goo Kang "Multi-class learning algorithm for deep neural network-based statistical parametric speech synthesis" in EUSIPCO, 2016
9 Domestic Conference Min-jae Hwang, JeeSok Lee, Misuk Lee, and Hong-Goo Kang "사전 분석법을 통한 스프레드 스펙트럼 기반 오디오 워터마킹 알고리즘의 성능 향상" in 한국음향학회 제 33회 음성통신 및 신호처리 학술대회, 2016