Papers

PARAN: Variational Autoencoder-based End-to-End Articulation-to-Speech System for Speech Intelligibility

International Conference
작성자
이지현
작성일
2024-06-13 11:26
조회
1323
Authors : Seyun Um, Doyeon Kim, Hong-Goo Kang

Year : 2024

Publisher / Conference : INTERSPEECH

Research area : Speech Signal Processing, Speech Synthesis, Multi-modal Signal Processing

Presentation/Publication date : 2024.09.03

Presentation : Poster

Deep learning-based articulation-to-speech (ATS) systems designed for individuals with speech disorders have been extensively researched in recent years. However, conventional methods have faced challenges in effectively representing the transformation in latent space across speech and electromagnetic articulography (EMA) domains, resulting in low speech quality. In this paper, we propose a variational autoencoder (VAE)-based end-to-end ATS model called PARAN that efficiently produces high-fidelity speech waveforms from EMA signals. Our model adjusts a prior distribution of latent representations from EMA signals to match a posterior distribution derived from speech waveforms utilizing a normalizing flow mechanism. To further enhance the clarity and intelligibility of the synthesized speech, we incorporate an additional loss function aimed at predicting phonetic information from EMA signals. Experimental results demonstrate that our model outperforms previous methods in terms of speech quality and intelligibility.
전체 370
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