no code implementations • WS 2019 • An Suresh, a Theertha, Brian Roark, Michael Riley, Vlad Schogol
Weighted finite automata (WFA) are often used to represent probabilistic models, such as n-gram language models, since they are efficient for recognition tasks in time and space.
no code implementations • WS 2019 • Lawrence Wolf-Sonkin, Vlad Schogol, Brian Roark, Michael Riley
The use of the Latin script for text entry of South Asian languages is common, even though there is no standard orthography for these languages in the script.
no code implementations • CL (ACL) 2021 • Ananda Theertha Suresh, Brian Roark, Michael Riley, Vlad Schogol
Weighted finite automata (WFA) are often used to represent probabilistic models, such as $n$-gram language models, since they are efficient for recognition tasks in time and space.
no code implementations • 5 Dec 2017 • Tara N. Sainath, Rohit Prabhavalkar, Shankar Kumar, Seungji Lee, Anjuli Kannan, David Rybach, Vlad Schogol, Patrick Nguyen, Bo Li, Yonghui Wu, Zhifeng Chen, Chung-Cheng Chiu
However, there has been little previous work comparing phoneme-based versus grapheme-based sub-word units in the end-to-end modeling framework, to determine whether the gains from such approaches are primarily due to the new probabilistic model, or from the joint learning of the various components with grapheme-based units.