1 citations · 1 across the 5 of their papers we have counts for
4 papers · 1 filter
Reducing the Gap Between Pretrained Speech Enhancement and Recognition Models Using a Real Speech-Trained Bridging Module
Zhongjian Cui, Chenrui Cui, Tianrui Wang +6
The information loss or distortion caused by single-channel speech enhancement (SE) harms the performance of automatic speech recognition (ASR). Observation addition (OA) is an eff…
Diffusion-Based Speech Enhancement with Joint Generative and Predictive Decoders
Hao Shi, Kazuki Shimada, Masato Hirano +6
Diffusion-based generative speech enhancement (SE) has recently received attention, but reverse diffusion remains time-consuming. One solution is to initialize the reverse diffusio…
Extending Audio Masked Autoencoders Toward Audio Restoration
Zhi Zhong, Hao Shi, Masato Hirano +5
Audio classification and restoration are among major downstream tasks in audio signal processing. However, restoration derives less of a benefit from pretrained models compared to…
Time-domain Speech Enhancement Assisted by Multi-resolution Frequency Encoder and Decoder
Hao Shi, Masato Mimura, Longbiao Wang +2
Time-domain speech enhancement (SE) has recently been intensively investigated. Among recent works, DEMUCS introduces multi-resolution STFT loss to enhance performance. However, so…