Learning Visual Styles from Audio-Visual Associations
Tingle Li , Yichen Liu , Andrew Owens , Hang Zhao
ECCV , 2022  
PDF / Project Page / Code
We learn from unlabeled data to manipulate the style of an image using sound.
Radio2Speech: High Quality Speech Recovery from Radio Frequency Signals
Running Zhao , Jiangtao Yu , Tingle Li , Hang Zhao , Edith C.H. Ngai
Interspeech , 2022  
PDF / Project Page
High-quality speech recovery system for millimeter-wave radar without deafness.
Modality Laziness: Everybody's Business is Nobody's Business
Chenzhuang Du , Jiaye Teng , Tingle Li , Yichen Liu , Yue Wang , Yang Yuan , Hang Zhao
arXiv , 2022  
PDF
With multi-modal data as inputs, the encoders from naive fusion training will suffer from learning insufficient representations of each modality.
Neural Dubber: Dubbing for Videos According to Scripts
Chenxu Hu , Qiao Tian , Tingle Li , Yuping Wang, Yuxuan Wang , Hang Zhao
NeurIPS , 2021  
PDF / Project Page / Press
Automatic video dubbing driven by a neural network.
CVC: Contrastive Learning for Non-parallel Voice Conversion
Tingle Li , Yichen Liu , Chenxu Hu , Hang Zhao
Interspeech , 2021 (ISCA Student Travel Grant)  
PDF / Project Page / Code
One-way GAN training for non-parallel voice conversion.
Sams-Net: A Sliced Attention-based Neural Network for Music Source Separation
Tingle Li , Jiawei Chen, Haowen Hou, Ming Li
ISCSLP , 2021 (Oral, Best Undergraduate Dissertation)  
PDF / Project Page
The scope of attention is narrowed down to the intra-chunk musical features that are most likely to affect each other.
The DKU Speech Activity Detection and Speaker Identification Systems for Fearless Steps Challenge Phase-02
Qingjian Lin , Tingle Li , Ming Li
Interspeech , 2020  
PDF / Leaderboard
SoTA performance for speech activity detection and speaker identification.
Atss-Net: Target Speaker Separation via Attention-based Neural Network
Tingle Li , Qingjian Lin , Yuanyuan Bao, Ming Li
Interspeech , 2020  
PDF / Project Page
Adapted Transformer to the speech separation for more efficient and generalizable performance.
Optimal Mapping Loss: A Faster Loss for End-to-End Speaker Diarization
Qingjian Lin , Tingle Li , Lin Yang, Junjie Wang, Ming Li
Odyssey , 2020  
PDF
A new mapping loss based on Hungarian algorithm that reduces time complexity while maintaining performance for speaker diarization.