Papers

Deep learning-based speech presence probability estimation for noise PSD estimation in single-channel speech enhancement

International Conference
2016~2020
작성자
한혜원
작성일
2018-05-01 16:35
조회
1536
Authors : Haemin Yang, Soyeon Choe, Keulbit Kim, Hong-Goo Kang

Year : 2018

Publisher / Conference : ICSigSys

In single-channel speech enhancement, it is essential to determine noise reduction factors to successfully remove noise while minimizing speech distortion. These factors are typically set by a function of noise power spectral density (PSD) in time frequency domain, and the state-of-the-art algorithm also introduces additional processes to estimate speech presence probability (SPP) to further enhance the estimation. Due to many tuning parameters, however, it is not easy to implement an algorithm that reliably estimates SPP in noise varying environment. We proposed a combination of deep learning network and an effective training method to enhance the performance of the SPP estimation module. The proposed approach is regarded as a hybrid approach, with the noise reduction factor still estimated by the conventional statistic-based single channel enhancement algorithms. The advantages and disadvantages of the proposed approach compared to deep learning approach of single channel speech enhancement are also investigated.
전체 356
103 International Conference Hyeonjoo Kang, Young-Sun Joo, Inseon Jang, Chunghyun Ahn, Hong-Goo Kang "A Study on Acoustic Parameter Selection Strategies to Improve Deep Learning-Based Speech Synthesis" in APSIPA, 2019
102 International Conference Min-Jae Hwang, Hong-Goo Kang "Parameter enhancement for MELP speech codec in noisy communication environment" in INTERSPEECH, 2019
101 International Conference Keulbit Kim, Jinkyu Lee, Jan Skoglund, Hong-Goo Kang "Model Order Selection for Wind Noise Reduction in Non-negative Matrix Factorization" in ITC-CSCC, 2019
100 International Conference Ohsung Kwon, Inseon Jang, ChungHyun Ahn, Hong-Goo Kang "Emotional Speech Synthesis Based on Style Embedded Tacotron2 Framework" in ITC-CSCC, 2019
99 International Conference Kyungguen Byun, Eunwoo Song, Jinseob Kim, Jae-Min Kim, Hong-Goo Kang "Excitation-by-SampleRNN Model for Text-to-Speech" in ITC-CSCC, 2019
98 International Conference Yang Yuan, Soo-Whan Chung, Hong-Goo Kang "Gradient-based active learning query strategy for end-to-end speech recognition" in ICASSP, 2019
97 International Conference Soo-Whan Chung, Joon Son Chung, Hong-Goo Kang "Perfect match: Improved cross-modal embeddings for audio-visual synchronisation" in ICASSP, 2019
96 International Conference Hyewon Han, Kyungguen Byun, Hong-Goo Kang "A Deep Learning-based Stress Detection Algorithm with Speech Signal" in Workshop on Audio-Visual Scene Understanding for Immersive Multimedia (AVSU’18), 2018
95 International Conference Min-Jae Hwang, Eunwoo Song, Jin-Seob Kim, Hong-Goo Kang "A Unified Framework for the Generation of Glottal Signals in Deep Learning-based Parametric Speech Synthesis Systems" in INTERSPEECH, 2018
94 International Conference Haemin Yang, Soyeon Choe, Keulbit Kim, Hong-Goo Kang "Deep learning-based speech presence probability estimation for noise PSD estimation in single-channel speech enhancement" in ICSigSys, 2018