Papers

Length-Normalized Representation Learning for Speech Signals

International Journal
2021~
작성자
dsp
작성일
2022-06-08 16:07
조회
1299
Authors : Kyungguen Byun, Seyun Um, Hong-Goo Kang

Year : 2022

Publisher / Conference : IEEE Access

Volume : 10

Page : 60362-60372

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

Presentation/Publication date : 2022.06.08

Presentation : None

In this study, we proposed a length-normalized representation learning method for speech and text to address the inherent problem of sequence-to-sequence models when the input and output sequences exhibit different lengths. To this end, the representations were constrained to a fixed-length shape by including length normalization and de-normalization processes in the pre- and post-network architecture of the transformer-based self-supervised learning framework. Consequently, this enabled the direct modelling of the relationships between sequences with different length without attention or recurrent network between representation domains. This method not only achieved the aforementioned regularized length effect but also achieved a data augmentation effect that effectively handled differently time-scaled input features. The performance of the proposed length-normalized representations on downstream tasks for speaker and phoneme recognition was investigated to verify the effectiveness of this method over conventional representation methods. In addition, to demonstrate the applicability of the proposed representation method to sequence-to-sequence modeling, a unified speech recognition and text-to-speech (TTS) system was developed. The unified system achieved a high accuracy on a frame-wise phoneme prediction and exhibited a promising potential for the generation of high-quality synthesized speech signals on the TTS.
전체 355
38 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
37 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
36 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
35 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
34 International Conference Hejung Yang, Hong-Goo Kang "On Fine-Tuning Pre-Trained Speech Models With EMA-Target Self-Supervised Loss" in ICASSP, 2024
33 International Journal Zainab Alhakeem, Se-In Jang, Hong-Goo Kang "Disentangled Representations in Local-Global Contexts for Arabic Dialect Identification" in Transactions on Audio, Speech, and Language Processing, 2024
32 International Conference Hong-Goo Kang, W. Bastiaan Kleijn, Jan Skoglund, Michael Chinen "Convolutional Transformer for Neural Speech Coding" in Audio Engineering Society Convention, 2023
31 International Conference Hong-Goo Kang, Jan Skoglund, W. Bastiaan Kleijn, Andrew Storus, Hengchin Yeh "A High-Rate Extension to Soundstream" in IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2023
30 International Conference Zhenyu Piao, Hyungseob Lim, Miseul Kim, Hong-goo Kang "PDF-NET: Pitch-adaptive Dynamic Filter Network for Intra-gender Speaker Verification" in APSIPA ASC, 2023
29 International Journal Hyungchan Yoon, Changhwan Kim, Seyun Um, Hyun-Wook Yoon, Hong-Goo Kang "SC-CNN: Effective Speaker Conditioning Method for Zero-Shot Multi-Speaker Text-to-Speech Systems" in IEEE Signal Processing Letters, vol.30, pp.593-597, 2023