Michael Levison


2018

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Natural Language Generation for Polysynthetic Languages: Language Teaching and Learning Software for Kanyen’kéha (Mohawk)
Greg Lessard | Nathan Brinklow | Michael Levison
Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages

Kanyen’kéha (in English, Mohawk) is an Iroquoian language spoken primarily in Eastern Canada (Ontario, Québec). Classified as endangered, it has only a small number of speakers and very few younger native speakers. Consequently, teachers and courses, teaching materials and software are urgently needed. In the case of software, the polysynthetic nature of Kanyen’kéha means that the number of possible combinations grows exponentially and soon surpasses attempts to capture variant forms by hand. It is in this context that we describe an attempt to produce language teaching materials based on a generative approach. A natural language generation environment (ivi/Vinci) embedded in a web environment (VinciLingua) makes it possible to produce, by rule, variant forms of indefinite complexity. These may be used as models to explore, or as materials to which learners respond. Generated materials may take the form of written text, oral utterances, or images; responses may be typed on a keyboard, gestural (using a mouse) or, to a limited extent, oral. The software also provides complex orthographic, morphological and syntactic analysis of learner productions. We describe the trajectory of development of materials for a suite of four courses on Kanyen’kéha, the first of which will be taught in the fall of 2018.

2014

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Time after Time: Representing Time in Literary Texts
Michael Levison | Greg Lessard
Proceedings of the 3rd Workshop on Computational Linguistics for Literature (CLFL)

2013

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Groundhog DAG: Representing Semantic Repetition in Literary Narratives
Greg Lessard | Michael Levison
Proceedings of the Workshop on Computational Linguistics for Literature

2004

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Generated Narratives for Computer-aided Language Teaching
Michael Levison | Greg Lessard
Proceedings of the Workshop on eLearning for Computational Linguistics and Computational Linguistics for eLearning