1 citations · 2 across the 7 of their papers we have counts for
7 papers
CleanMel: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR
Nian Shao, Rui Zhou, Pengyu Wang +4
In this work, we propose CleanMel, a single-channel Mel-spectrogram denoising and dereverberation network for improving both speech quality and automatic speech recognition (ASR) p…
LS-EEND: Long-Form Streaming End-to-End Neural Diarization with Online Attractor Extraction
Di Liang, Xiaofei Li
This work proposes a frame-wise online/streaming end-to-end neural diarization (EEND) method, which detects speaker activities in a frame-in-frame-out fashion. The proposed model m…
Multichannel Long-Term Streaming Neural Speech Enhancement for Static and Moving Speakers
Changsheng Quan, Xiaofei Li
In this work, we extend our previously proposed offline SpatialNet for long-term streaming multichannel speech enhancement in both static and moving speaker scenarios. SpatialNet e…
Mel-FullSubNet: Mel-Spectrogram Enhancement for Improving Both Speech Quality and ASR
Rui Zhou, Xian Li, Ying Fang +1
In this work, we propose Mel-FullSubNet, a single-channel Mel-spectrogram denoising and dereverberation network for improving both speech quality and automatic speech recognition (…
RVAE-EM: Generative speech dereverberation based on recurrent variational auto-encoder and convolutive transfer function
Pengyu Wang, Xiaofei Li
In indoor scenes, reverberation is a crucial factor in degrading the perceived quality and intelligibility of speech. In this work, we propose a generative dereverberation method.…
Fine-tune the pretrained ATST model for sound event detection
Nian Shao, Xian Li, Xiaofei Li
Sound event detection (SED) often suffers from the data deficiency problem. The recent baseline system in the DCASE2023 challenge task 4 leverages the large pretrained self-supervi…
Self-supervised Audio Teacher-Student Transformer for Both Clip-level and Frame-level Tasks
Xian Li, Nian Shao, Xiaofei Li
Self-supervised learning (SSL) has emerged as a popular approach for learning audio representations. One goal of audio self-supervised pre-training is to transfer knowledge to down…