Tingle Li

I am a third-year CS Ph.D. student at UC Berkeley, advised by Gopala Anumanchipalli. I am a part of Berkeley Artificial Intelligence Research (BAIR) Lab, where I have been fortunate to collaborate with Andrew Owens.

Previously, I had the privilege to work with Hang Zhao from IIIS, Tsinghua University and Ming Li from Duke University.

My research focuses on auditory perception, particularly sound texture, which is often studied with vision. My long-term goal is to understand how humans derive information from sound.

Publications

	Self-Supervised Audio-Visual Soundscape Stylization Tingle Li, Renhao Wang, Po-Yao Huang, Andrew Owens, Gopala Anumanchipalli ECCV, 2024 PDF / Project Page Restyle a sound to fit with another scene, using an audio-visual conditional example taken from that scene.
	Deep Speech Synthesis from MRI-Based Articulatory Representations Peter Wu, Tingle Li, Yijing Lu, Yubin Zhang, Jiachen Lian, Alan Black, Louis Goldstein, Shinji Watanabe, Gopala Anumanchipalli Interspeech, 2023 PDF We synthesize speech from MRI videos.
	On Uni-Modal Feature Learning in Supervised Multi-Modal Learning Chenzhuang Du, Jiaye Teng, Tingle Li, Yichen Liu, Tianyuan Yuan, Yue Wang, Yang Yuan, Hang Zhao ICML, 2023 PDF We enhance the generalization ability of multimodal models by categorizing the features into uni-modal and paired.
	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.
	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.

Last updated Oct. 2024.
Template from Jon Barron.