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Distilling weighted finite automata from arbitrary probabilistic models
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.
Latin script keyboards for South Asian languages with finite-state normalization
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.
Approximating probabilistic models as weighted finite automata
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 Need for a Lexicon? Evaluating the Value of the Pronunciation Lexica in End-to-End Models
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.
