I am a research scientist at Google studying natural language processing.

Previously, I was a Ph.D. student in the Natural Language Processing Group at UC Berkeley, advised by Dan Klein. My thesis research was on decoding silent speech with electromyography. This work aimed to recognize silently mouthed words and turn them into audible speech or text, using electrical signals from muscles of the face. I also worked on a range of other topics, including language grounding, semantic parsing, and syntactic parsing. I did my undergraduate studies at MIT.

Email: dgaddy@google.com

Silent Speech Publications

Digital Voicing of Silent Speech
David Gaddy and Dan Klein
Best Paper Award EMNLP 2020. [code] [data] [video]

An Improved Model for Voicing Silent Speech
David Gaddy and Dan Klein
ACL 2021. [code]

Other Publications

Overcoming Conflicting Data when Updating a Neural Semantic Parser
David Gaddy, Alex Kouzemtchenko, Pavankumar Reddy Muddireddy, Prateek Kolhar, and Rushin Shah
Workshop on NLP for Conversational AI, EMNLP 2021. [data]

Interactive Assignments for Teaching Structured Neural NLP
David Gaddy, Daniel Fried, Nikita Kitaev, Mitchell Stern, Rodolfo Corona, John DeNero, and Dan Klein
Teaching NLP Workshop, NAACL 2021. [materials]

Pre-Learning Environment Representations for Data-Efficient Neural Instruction Following
David Gaddy and Dan Klein
ACL 2019. [code] [slides] [blog]

What’s Going On in Neural Constituency Parsers? An Analysis
David Gaddy, Mitchell Stern, and Dan Klein
NAACL 2018. [code] [poster]

Ten Pairs to Tag - Multilingual POS Tagging via Coarse Mapping between Embeddings
Yuan Zhang, David Gaddy, Regina Barzilay, and Tommi Jaakkola
NAACL 2016. [code]