David Harwath
Assistant Professor
David Harwath's research interests are in the areas of automatic speech recognition, spoken language understanding, and multi-modal machine learning. His work aims to develop models of speech and language that are robust, flexible, and capable of learning on the fly from multiple input modalities. He holds a B.S. in Electrical Engineering from the University of Illinois at Urbana-Champaign, a S.M. in Computer Science from MIT, and a Ph.D. in Computer Science from MIT.
Research
Research Areas:
Research Interests:
Automatic speech recognition, spoken language understanding, multi-modal and embodied machine learning (speech, environmental sound, vision)
Select Publications
. 2020. Learning Hierarchical Discrete Linguistic Units from Visually-Grounded Speech. ICLR 2020.
. 2019. Transfer Learning from Audio-Visual Grounding to Speech Recognition. Interspeech.
. 2019. Towards Bilingual Lexicon Discovery From Visually Grounded Speech Audio. Interspeech.
. 2019. Learning Words by Drawing Images. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
. 2019. Jointly Discovering Visual Objects and Spoken Words from Raw Sensory Input. International Journal of Computer Vision.
Awards & Honors
- 2018 - George M. Sprowls Award for best doctoral thesis in computer science, MIT