About Speaker
Full Time Graduate Researcher, part time hacker and FOSS enthusiast.
I write code for Watson and do a bunch of other things at their lab (mostly deals with algorithm,NLP, Ontologies,reading papers among other stuff). At present I am a doctoral student at RICE University. I also try to contribute to Mozilla (primarily on Firefox OS) in my free time.
About the Topic
Language input for mobile devices has always been a challenge on how to provide intuitive experience along with the easy of type. One approach towards that end is predictive text input. But predictions are as good as the wordlist that it gets generated from. Often it becomes a much harder problem to implement the same approach for localized languages like Hindi,Bengali (India, Bangladesh) and languages that require IME to type effectively. One approach is to learn from users typing preference and improve the dictionary weight-age to improve prediction. This talk will discuss upon how this can be implemented in Firefox OS and how the same approach can be used for openweb apps universally without locking in to any specific language. We also will briefly discuss how it manages to improve localized language predictions and the challenges some transliteration system faces along with how we can tackle them.