6 citations · 11 across the 4 of their papers we have counts for
7 papers · 1 filter
Cross-domain Single-channel Speech Enhancement Model with Bi-projection Fusion Module for Noise-robust ASR
Fu-An Chao, Jeih-weih Hung, Berlin Chen
In recent decades, many studies have suggested that phase information is crucial for speech enhancement (SE), and time-domain single-channel speech enhancement techniques have show…
TENET: A Time-reversal Enhancement Network for Noise-robust ASR
Fu-An Chao, Shao-Wei Fan Jiang, Bi-Cheng Yan +2
Due to the unprecedented breakthroughs brought about by deep learning, speech enhancement (SE) techniques have been developed rapidly and play an important role prior to acoustic m…
Incorporating Broad Phonetic Information for Speech Enhancement
Yen-Ju Lu, Chien-Feng Liao, Xugang Lu +2
In noisy conditions, knowing speech contents facilitates listeners to more effectively suppress background noise components and to retrieve pure speech signals. Previous studies ha…
Waveform-based Voice Activity Detection Exploiting Fully Convolutional networks with Multi-Branched Encoders
Cheng Yu, Kuo-Hsuan Hung, I-Fan Lin +3
In this study, we propose an encoder-decoder structured system with fully convolutional networks to implement voice activity detection (VAD) directly on the time-domain waveform. T…
Time-Domain Multi-modal Bone/air Conducted Speech Enhancement
Cheng Yu, Kuo-Hsuan Hung, Syu-Siang Wang +3
Previous studies have proven that integrating video signals, as a complementary modality, can facilitate improved performance for speech enhancement (SE). However, video clips usua…
Distributed Microphone Speech Enhancement based on Deep Learning
Syu-Siang Wang, Yu-You Liang, Jeih-weih Hung +3
Speech-related applications deliver inferior performance in complex noise environments. Therefore, this study primarily addresses this problem by introducing speech-enhancement (SE…