OD-SLA-2.1

CycleGAN-based Non-parallel Speech Enhancement with an Adaptive Attention-in-attention Mechanism

Guochen Yu, Yutian Wang, Hui Wang, Qin Zhang, Communication University of China, China; Chengshi Zheng, Institute of Acoustics, Chinese Academy of Sciences, China
Session:
Speech Enhancement
Track:
Speech, Language, and Audio (SLA)
Session Time:
Wed, 15 Dec, 14:40 - 16:40 Japan Standard Time (UTC +9)
Wed, 15 Dec, 05:40 - 07:40 Coordinated Universal Time
Wed, 15 Dec, 00:40 - 02:40 Eastern Standard Time (UTC -5)
Tue, 14 Dec, 21:40 - 23:40 Pacific Standard Time (UTC -8)
Session Chair:
Jun Du, University of Science and Technology of China
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Session OD-SLA-2
WE2.OD-A.1: CycleGAN-based Non-parallel Speech Enhancement with an Adaptive Attention-in-attention Mechanism
Guochen Yu, Yutian Wang, Hui Wang, Qin Zhang, Communication University of China, China; Chengshi Zheng, Institute of Acoustics, Chinese Academy of Sciences, China
WE2.OD-A.2: A Robust Maximum Likelihood Distortionless Response Beamformer based on a Complex Generalized Gaussian Distribution
Weixin Meng, Chengshi Zheng, Xiaodong Li, Key Laboratory of Noise and Vibration Research, Institute of Acoustics, Chinese Academy of Science, Beijing, 100190, Chinaï¼›University of Chinese Academy of Sciences, Beijing, China, China
WE2.OD-A.3: SPEECH ENHANCEMENT BASED ON MASKING APPROACH CONSIDERING SPEECH QUALITY AND ACOUSTIC CONFIDENCE FOR NOISY SPEECH RECOGNITION
Shih-Chuan Chu, Chung-Hsien Wu, Yun-Wen Lin, National Cheng Kung University, Taiwan
WE2.OD-A.4: DNN-BASED LINEAR PREDICTION RESIDUAL ENHANCEMENT FOR SPEECH DEREVERBERATION
Xinyang Feng, Nuo Li, Zunwen He, Yan Zhang, Wancheng Zhang, Beijing Institute of Technology, China
WE2.OD-A.5: Mandarin Electro-Laryngeal Speech Enhancement based on Statistical Voice Conversion and Manual Tone Control
Zhaopeng Qian, Haijun Niu, Shaochuan Zhang, Beihang University, China; Li Wang, Beijing Research Center of Urban System Engineering, China; Kazuhiro Kobayashi, Tomoki Toda, Nagoya University, Japan
WE2.OD-A.6: Incorporating Multi-Target in Multi-Stage Speech Enhancement Model for Better Generalization
Lu Zhang, Mingjiang Wang, Zehua Zhang, Xuyi Zhuang, Harbin Institute of Technology, Shenzhen, China; Andong Li, Institute of Acoustics, Chinese Academy of Sciences, China
WE2.OD-A.7: Low-Power Convolutional Recurrent Neural Network For Monaural Speech Enhancement
Fei Gao, Haixin Guan, Unisound AI Technology Co. Ltd, China; , ,
WE2.OD-A.8: Multi-channel Speech Enhancement with 2-D Convolutional Time-frequency Domain Features and a Pre-trained Acoustic Model
Quandong Wang, Junnan Wu, Zhao Yan, Sichong Qian, Liyong Guo, Lichun Fan, Weiji Zhuang, Peng Gao, Yujun Wang, Xiaomi Corporation, China
WE2.OD-A.9: Processing Phoneme Specific Segments for Cleft Lip and Palate Speech Enhancement
Protima Nomo Sudro, Rohit Sinha, Indian Institute of Technology Guwahati, India; S R Mahadeva Prasanna, Indian Institute of Technology Dharwad, India
WE2.OD-A.10: Speech Enhancement by Noise Self-Supervised Rank-Constrained Spatial Covariance Matrix Estimation via Independent Deeply Learned Matrix Analysis
Sota Misawa, Norihiro Takamune, Tomohiko Nakamura, Hiroshi Saruwatari, The University of Tokyo, Japan; Daichi Kitamura, National Institute of Technology, Japan; Masakazu Une, University of Tsukuba, Japan; Shoji Makino, Waseda University, Japan
WE2.OD-A.11: CAUSAL DISTORTIONLESS RESPONSE BEAMFORMING BY ALTERNATING DIRECTION METHOD OF MULTIPLIERS
Yoshiki Masuyama, Kouei Yamaoka, Yuma Kinoshita, Nobutaka Ono, Tokyo Metropolitan University​, Japan
WE2.OD-A.12: STACKED U-NET WITH HIGH-LEVEL FEATURE TRANSFER FOR PARAMETER EFFICIENT SPEECH ENHANCEMENT
Jinyoung Lee, Hong-Goo Kang, Yonsei University, Korea, Republic of
WE2.OD-A.13: EXTENSION OF VIRTUAL MICROPHONE TECHNIQUE TO MULTIPLE REAL MICROPHONES AND INVESTIGATION OF THE IMPACT OF PHASE AND AMPLITUDE INTERPOLATION ON SPEECH ENHANCEMENT
Hanako Segawa, Takeshi Yamada, University of Tsukuba, Japan; Li Li, NTT Corporation, Japan; Shoji Makino, University of Tsukuba, Waseda University, Japan
WE2.OD-A.14: Comparative Study on DNN-based Minimum Variance Beamforming Robust to Small Movements of Sound Sources
Kohei Saijo, Tetsunori Kobayashi, Tetsuji Ogawa, Waseda University, Japan; Kazuhiro Katagiri, Masaru Fujieda, OKI Electric Industry Corporation, Japan
WE2.OD-A.15: IMPROVEMENTS TO NON-INTRUSIVE INTELLIGIBILITY PREDICTION FOR REVERBERANT SPEECH
Kazushi Nakazawa, Kazuhiro Kondo, Yamagata University, Japan