Maxim Roy

Maxim Roy
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Main area of research
Natural language & AI

Maxim Roy is a Senior NL Research Engineer in the Clinical Language Understanding group with research interests in the areas of Clinical NLP, Statistical Machine Translation, Information Extraction, Co-reference Resolution, Text Analytics, Semi-supervised and Active Learning. Prior to joining Nuance, Maxim was a Researcher and Team Lead at NorthSide inc. His current area of research is in clinical NLP. He has a B.S. and M.S.in computer science from the University of Windsor, and a Ph.D. in Computing Science from Simon Fraser University.

Selected articles

Phrase-based statistical machine translation for a low-density language pair

English that incorporates a novel transliteration module, and a specialized component for handling prepositions and Bangla compound words. We evaluate our components through their impact

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Active learning for statistical phrase-based machine translation

Statistical machine translation (SMT) models need large bilingual corpora for training, which are unavailable for some language pairs. This paper provides the first serious experimental

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A Semi-supervised approach to Bengali-English phrase-based statistical Machine translation

Large amounts of bilingual data and monolingual data in the target language are usually used to train statistical machine translation systems. In this paper we

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LRRP SpeechWebs

This paper describes a new architecture for accessing hyperlinked speech-accessible knowledge sources that are distributed over the Internet. It differs from the use of speech

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Extending Montague semantics for use in natural-language database-query processing

Montague’s semantics has been used in the past for constructing natural-language processors in higher-order functional languages. This paper describes the work done and progress so

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