| Accent-robust automatic speech recognition using supervised and unsupervised wav2vec embeddings J Li, V Manohar, P Chitkara, A Tjandra, M Picheny, F Zhang, X Zhang, ... arXiv preprint arXiv:2110.03520, 2021 | 17 | 2021 |
| Analysis of acoustic and voice quality features for the classification of infant and mother vocalizations J Li, M Hasegawa-Johnson, NL McElwain Speech communication 133, 41-61, 2021 | 10 | 2021 |
| Autosegmental neural nets: Should phones and tones be synchronous or asynchronous? J Li, M Hasegawa-Johnson Interspeech 2020, 2020 | 6 | 2020 |
| An embodied, platform-invariant architecture for connecting high-level spatial commands to platform articulation AJ Sher, U Huzaifa, J Li, V Jain, A Zurawski, A LaViers Robotics and Autonomous Systems 119, 263-277, 2019 | 6 | 2019 |
| Towards robust family-infant audio analysis based on unsupervised pretraining of wav2vec 2.0 on large-scale unlabeled family audio J Li, M Hasegawa-Johnson, NL McElwain arXiv preprint arXiv:2305.12530, 2023 | 5 | 2023 |
| Preliminary Technical Validation of LittleBeats™: A Multimodal Sensing Platform to Capture Cardiac Physiology, Motion, and Vocalizations B Islam, NL McElwain, J Li, MI Davila, Y Hu, K Hu, JM Bodway, A Dhekne, ... Sensors 24 (3), 901, 2024 | 1 | 2024 |
| Visualizations of Complex Sequences of Family-Infant Vocalizations Using Bag-of-Audio-Words Approach Based on Wav2vec 2.0 Features J Li, M Hasegawa-Johnson, NL McElwain arXiv preprint arXiv:2203.15183, 2022 | 1 | 2022 |
| A comparable phone set for the timit dataset discovered in clustering of listen, attend and spell J Li, M Hasegawa-Johnson NIPS 2018 Workshop IRASL, 2018 | 1 | 2018 |
| Analysis of Self-Supervised Speech Models on Children's Speech and Infant Vocalizations J Li, M Hasegawa-Johnson, NL McElwain arXiv preprint arXiv:2402.06888, 2024 | | 2024 |
| Enhancing Child Vocalization Classification in Multi-Channel Child-Adult Conversations Through Wav2vec2 Children ASR Features J Li, M Hasegawa-Johnson, K Karahalios arXiv preprint arXiv:2309.07287, 2023 | | 2023 |
| Listen, Decipher and Sign: Toward Unsupervised Speech-to-Sign Language Recognition L Wang, J Ni, H Gao, J Li, KC Chang, X Fan, J Wu, M Hasegawa-Johnson, ... Findings of the Association for Computational Linguistics: ACL 2023, 6785-6800, 2023 | | 2023 |
| Autosegmental Neural Nets 2.0: An Extensive Study of Training Synchronous and Asynchronous Phones and Tones for Under-Resourced Tonal Languages J Li, M Hasegawa-Johnson IEEE/ACM Transactions on Audio, Speech, and Language Processing 30, 1918-1926, 2022 | | 2022 |
Mark Hasegawa-JohnsonProfessor of Electrical and Computer Engineering, University of IllinoisBestätigte E-Mail-Adresse bei illinois.edu
