Papers

A Joint Learning Algorithm for Complex-Valued T-F Masks in Deep Learning-Based Single-Channel Speech Enhancement Systems

International Journal
2016~2020
작성자
이진영
작성일
2019-06-01 22:12
조회
426
Authors : Jinkyu Lee, Hong-Goo Kang

Year : 2019

Publisher / Conference : IEEE/ACM Transactions on Audio, Speech, and Language Processing

Volume : 27, issue 6

Page : 1098-1108

This paper presents a joint learning algorithm for complex-valued time-frequency (T-F) masks in single-channel speech enhancement systems. Most speech enhancement algorithms operating in a single-channel microphone environment aim to enhance the magnitude component in a T-F domain, while the input noisy phase component is used directly without any processing. Consequently, the mismatch between the processed magnitude and the unprocessed phase degrades the sound quality. To address this issue, a learning method of targeting a T-F mask that is defined in a complex domain has recently been proposed. However, due to a wide dynamic range and an irregular spectrogram pattern of the complex-valued T-F mask, the learning process is difficult even with a large-scale deep learning network. Moreover, the learning process targeting the T-F mask itself does not directly minimize the distortion in spectra or time domains. In order to address these concerns, we focus on three issues: 1) an effective estimation of complex numbers with a wide dynamic range; 2) a learning method that is directly related to speech enhancement performance; and 3) a way to resolve the mismatch between the estimated magnitude and phase spectra. In this study, we propose objective functions that can solve each of these issues and train the network by minimizing them with a joint learning framework. The evaluation results demonstrate that the proposed learning algorithm achieves significant performance improvement in various objective measures and subjective preference listening test.
전체 327
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8 International Journal Soo-Whan Chung, Joon Son Chung, Hong Goo Kang "Perfect Match: Self-Supervised Embeddings for Cross-Modal Retrieval" in IEEE Journal of Selected Topics in Signal Processing, vol.14, issue 3, 2020
7 International Journal Ohsung Kwon, Inseon Jang, ChungHyun Ahn, Hong-Goo Kang "An Effective Style Token Weight Control Technique for End-to-End Emotional Speech Synthesis" in IEEE Signal Processing Letters, vol.26, issue 9, pp.1383-1387, 2019
6 International Journal Jinkyu Lee, Hong-Goo Kang "A Joint Learning Algorithm for Complex-Valued T-F Masks in Deep Learning-Based Single-Channel Speech Enhancement Systems" in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.27, issue 6, pp.1098-1108, 2019
5 International Journal Seung-Chul Shin, Jinkyu Lee, Soyeon Choe, Hyuk In Yang, Jihee Min, Ki-Yong Ahn, Justin Y. Jeon, Hong-Goo Kang "Dry Electrode-Based Body Fat Estimation System with Anthropometric Data for Use in a Wearable Device" in Sensors, vol.19, issue 9, 2019
4 International Journal Jinkyu Lee, Jan Skoglund, Turaj Shabestary, Hong-Goo Kang "Phase-Sensitive Joint Learning Algorithms for Deep Learning-Based Speech Enhancement" in IEEE Signal Processing Letters, vol.25, issue 8, pp.1276-1280, 2018
3 International Journal JeeSok Lee, Soo-Whan Chung, Min-Seok Choi, Hong-Goo Kang "Generic uniform search grid generation algorithm for far-field source localization" in The Journal of the Acoustical Society of America, vol.143, 2018
2 International Journal Min-Jae Hwang, JeeSok Lee, MiSuk Lee, Hong-Goo Kang "SVD-Based Adaptive QIM Watermarking on Stereo Audio Signals" in IEEE Transactions on Multimedia, vol.20, issue 1, pp.45-54, 2018
1 International Journal Eunwoo Song, Frank K. Soong, Hong-Goo Kang "Effective Spectral and Excitation Modeling Techniques for LSTM-RNN-Based Speech Synthesis Systems" in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.25, issue 11, pp.2152-2161, 2017