activity
20192022
most citedImproving Multi-Modal Learning with Uni-Modal Teachers

25 citations · 33 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2022

Learning Visual Styles from Audio-Visual Associations

Tingle Li, Yichen Liu, Andrew Owens +1

From the patter of rain to the crunch of snow, the sounds we hear often convey the visual textures that appear within a scene. In this paper, we present a method for learning visua…

cs.LG202125 cited

Improving Multi-Modal Learning with Uni-Modal Teachers

Chenzhuang Du, Tingle Li, Yichen Liu +4

Learning multi-modal representations is an essential step towards real-world robotic applications, and various multi-modal fusion models have been developed for this purpose. Howev…

cs.SD20203 cited

CVC: Contrastive Learning for Non-parallel Voice Conversion

Tingle Li, Yichen Liu, Chenxu Hu +1

Cycle consistent generative adversarial network (CycleGAN) and variational autoencoder (VAE) based models have gained popularity in non-parallel voice conversion recently. However,…

eess.AS20205 cited

Atss-Net: Target Speaker Separation via Attention-based Neural Network

Tingle Li, Qingjian Lin, Yuanyuan Bao +1

Recently, Convolutional Neural Network (CNN) and Long short-term memory (LSTM) based models have been introduced to deep learning-based target speaker separation. In this paper, we…

eess.AS2019

Sams-Net: A Sliced Attention-based Neural Network for Music Source Separation

Tingle Li, Jiawei Chen, Haowen Hou +1

Convolutional Neural Network (CNN) or Long short-term memory (LSTM) based models with the input of spectrogram or waveforms are commonly used for deep learning based audio source s…