Izhak Shafran
Izhak Shafran is a researcher working on deep learning for large language modeling, focused on novel models architectures.
Before joining Google, he was a faculty member at the Oregon Health & Science University (OHSU) and the Johns Hopkins University (JHU).
Before joining Google, he was a faculty member at the Oregon Health & Science University (OHSU) and the Johns Hopkins University (JHU).
Authored Publications
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Google
Description-Driven Task-Oriented Dialog Modeling
Dian Yu
Mingqiu Wang
Abhinav Kumar Rastogi
Yonghui Wu
2022
The Medical Scribe: Corpus Development and Model Performance Analyses
Amanda Perry
Ashley Robson Domin
Chris Co
Gang Li
Hagen Soltau
Justin Stuart Paul
Lauren Keyes
Linh Tran
Mark David Knichel
Mingqiu Wang
Nan Du
Rayman Huang
Proc. Language Resources and Evaluation, 2020
Google COVID-19 Search Trends Symptoms Dataset: Anonymization Process Description
Akim Kumok
Chaitanya Kamath
Charlotte Stanton
Damien Desfontaines
Evgeniy Gabrilovich
Gerardo Flores
Gregory Alexander Wellenius
Ilya Eckstein
John S. Davis
Katie Everett
Krishna Kumar Gadepalli
Rayman Huang
Shailesh Bavadekar
Thomas Ludwig Roessler
Venky Ramachandran
Yael Mayer
Arxiv.org, N/A (2020)
Audio De-identification: A New Entity Recognition Task
Ido Cohn
Gang Li
Tzvika Hartman
NAACL (2019)
Extracting Symptoms and their Status from Clinical Conversations
Nan Du
Linh Tran
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy (2019), pp. 915-9125
Acoustic Modeling for Google Home
Joe Caroselli
Kean Chin
Chanwoo Kim
Olivier Siohan
Mitchel Weintraub
Erik McDermott
INTERSPEECH 2017 (2017)
Raw Multichannel Processing Using Deep Neural Networks
Kean Chin
Chanwoo Kim
New Era for Robust Speech Recognition: Exploiting Deep Learning, Springer (2017)
