Papers

FluentTTS: Text-dependent Fine-grained Style Control for Multi-style TTS

International Conference
작성자
dsp
작성일
2022-06-16 17:07
조회
1270
Authors : Changhwan Kim, Seyun Um, Hyungchan Yoon, Hong-goo Kang

Year : 2022

Publisher / Conference : INTERSPEECH

Research area : Speech Signal Processing, Text-to-Speech, Speech Synthesis


Presentation : Poster

In this paper, we propose a method to flexibly control the local prosodic variation of a neural text-to-speech (TTS) model. To provide expressiveness for synthesized speech, conventional TTS models utilize utterance-wise global style embeddings that are obtained by compressing frame-level embeddings along the time axis. However, since utterance-wise global features do not contain sufficient information to represent the characteristics of word-level local features, they are not appropriate for direct use on controlling prosody at a fine scale. In multi-style TTS models, it is very important to have the capability to control local prosody because it plays a key role in finding the most appropriate text-to-speech pair among many one-to-many mapping candidates.
To explicitly present local prosodic characteristics to the contextual information of the corresponding input text, we propose a module to predict the fundamental frequency (F0) of each text by conditioning on the utterance-wise global style embedding. We also estimate multi-style embeddings using a multi-style encoder, which takes as inputs both a global utterance-wise embedding and a local F0 embedding. Our multi-style embedding enhances the naturalness and expressiveness of synthesized speech and is able to control prosody styles at the word-level or phoneme -level.
전체 360
360 International Conference Seyun Um, Doyeon Kim, Hong-Goo Kang "PARAN: Variational Autoencoder-based End-to-End Articulation-to-Speech System for Speech Intelligibility" in INTERSPEECH, 2024
359 International Conference Jihyun Kim, Stijn Kindt, Nilesh Madhu, Hong-Goo Kang "Enhanced Deep Speech Separation in Clustered Ad Hoc Distributed Microphone Environments" in INTERSPEECH, 2024
358 International Conference Woo-Jin Chung, Hong-Goo Kang "Speaker-Independent Acoustic-to-Articulatory Inversion through Multi-Channel Attention Discriminator" in INTERSPEECH, 2024
357 International Conference Juhwan Yoon, Woo Seok Ko, Seyun Um, Sungwoong Hwang, Soojoong Hwang, Changhwan Kim, Hong-Goo Kang "UNIQUE : Unsupervised Network for Integrated Speech Quality Evaluation" in INTERSPEECH, 2024
356 International Conference Yanjue Song, Doyeon Kim, Hong-Goo Kang, Nilesh Madhu "Spectrum-aware neural vocoder based on self-supervised learning for speech enhancement" in EUSIPCO, 2024
355 International Conference Hyewon Han, Naveen Kumar "A cross-talk robust multichannel VAD model for multiparty agent interactions trained using synthetic re-recordings" in Hands-free Speech Communication and Microphone Arrays (HSCMA, Satellite workshop in ICASSP), 2024
354 International Conference Yanjue Song, Doyeon Kim, Nilesh Madhu, Hong-Goo Kang "On the Disentanglement and Robustness of Self-Supervised Speech Representations" in International Conference on Electronics, Information, and Communication (ICEIC) (*awarded Best Paper), 2024
353 International Conference Yeona Hong, Miseul Kim, Woo-Jin Chung, Hong-Goo Kang "Contextual Learning for Missing Speech Automatic Speech Recognition" in International Conference on Electronics, Information, and Communication (ICEIC), 2024
352 International Conference Juhwan Yoon, Seyun Um, Woo-Jin Chung, Hong-Goo Kang "SC-ERM: Speaker-Centric Learning for Speech Emotion Recognition" in International Conference on Electronics, Information, and Communication (ICEIC), 2024
351 International Conference Hejung Yang, Hong-Goo Kang "On Fine-Tuning Pre-Trained Speech Models With EMA-Target Self-Supervised Loss" in ICASSP, 2024