Papers

Stacked U-Net with High-level Feature Transfer for Parameter Efficient Speech Enhancement

International Conference
2021~
작성자
김화연
작성일
2021-09-01 14:48
조회
562
Authors : Jinyoung Lee and Hong-Goo Kang

Year : 2021

Publisher / Conference : APSIPA ASC

Research area : Speech Signal Processing, Speech Enhancement

In this paper, we present a stacked U-Net structure-based speech enhancement algorithm with parameter reduction and real-time processing. To significantly reduce the number of network parameters, we propose a stacked structure in which several shallow U-Nets with fewer convolutional layer channels are cascaded. However, simply stacking the small-scale U-Nets cannot sufficiently compensate for the performance loss caused by the lack of parameters. To overcome this problem, we propose a high-level feature transfer method that passes all the multi-channel output features, which are obtained before passing through the intermediate output layer, to the next stage.Furthermore, our proposed model can process analysis frames with short lengths because its down-sampling and up-sampling blocks are much smaller than the conventional Wave U-Net method; theses smaller layers make our proposed model suitable for low-delay online processing. Experiments show that our proposed method outperforms the conventional Wave U-Net method on almost all objective measures and requires only 7.21%of the network parameters when compared to the conventional method. In addition, our model can be successfully implemented in real time on both GPU and CPU environments.
전체 327
327 International Journal Jinyoung Lee, Hong-Goo Kang "Two-Stage Refinement of Magnitude and Complex Spectra for Real-Time Speech Enhancement" in IEEE Signal Processing Letters, vol.29, pp.2188-2192, 2022
326 International Conference Hyeon-Kyeong Shin, Hyewon Han, Doyeon Kim, Soo-Whan Chung, Hong-Goo Kang "Learning Audio-Text Agreement for Open-vocabulary Keyword Spotting" in INTERSPEECH (*Best Student Paper Finalist), 2022
325 International Conference Changhwan Kim, Se-yun Um, Hyungchan Yoon, Hong-goo Kang "FluentTTS: Text-dependent Fine-grained Style Control for Multi-style TTS" in INTERSPEECH, 2022
324 International Conference Miseul Kim, Zhenyu Piao, Seyun Um, Ran Lee, Jaemin Joh, Seungshin Lee, Hong-Goo Kang "Light-Weight Speaker Verification with Global Context Information" in INTERSPEECH, 2022
323 International Journal Kyungguen Byun, Se-yun Um, Hong-Goo Kang "Length-Normalized Representation Learning for Speech Signals" in IEEE Access, vol.10, pp.60362-60372, 2022
322 International Conference Doyeon Kim, Hyewon Han, Hyeon-Kyeong Shin, Soo-Whan Chung, Hong-Goo Kang "Phase Continuity: Learning Derivatives of Phase Spectrum for Speech Enhancement" in ICASSP, 2022
321 International Conference Chanwoo Lee, Hyungseob Lim, Jihyun Lee, Inseon Jang, Hong-Goo Kang "Progressive Multi-Stage Neural Audio Coding with Guided References" in ICASSP, 2022
320 International Conference Jihyun Lee, Hyungseob Lim, Chanwoo Lee, Inseon Jang, Hong-Goo Kang "Adversarial Audio Synthesis Using a Harmonic-Percussive Discriminator" in ICASSP, 2022
319 International Conference Jinyoung Lee and Hong-Goo Kang "Stacked U-Net with High-level Feature Transfer for Parameter Efficient Speech Enhancement" in APSIPA ASC, 2021
318 International Conference Huu-Kim Nguyen, Kihyuk Jeong, Se-Yun Um, Min-Jae Hwang, Eunwoo Song, Hong-Goo Kang "LiteTTS: A Decoder-free Light-weight Text-to-wave Synthesis Based on Generative Adversarial Networks" in INTERSPEECH, 2021