Indigenous language technologies in Canada: Assessment, challenges, and successes

5302

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nan

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AbstractIn this article, we discuss which text, speech, and image technologies have been developed, and would be feasible to develop, for the approximately 60 Indigenous languages spoken in Canada. In particular, we concentrate on technologies that may be feasible to develop for most or all of these languages, not just those that may be feasible for the few most-resourced of these. We assess past achievements and consider future horizons for Indigenous language transliteration, text prediction, spell-checking, approximate search, machine translation, speech recognition, speaker diarization, speech synthesis, optical character recognition, and computer-aided language learning.

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Proceedings of the 27th International Conference on Computational Linguistics, pages 2620–2632 Santa Fe, New Mexico, USA, August 20-26, 2018. 2620 Indigenous language technologies in Canada: Assessment, challenges, and successes Patrick Littell National Research Council of Canada 1200 Montreal Road Ottawa, ON, K1A 0R6 patrick.littell@nrc.gc.ca Anna Kazantseva National Research Council of Canada 5071 West Saanich Road Victoria, BC, V9E 2E7 anna.kazantseva@nrc.gc.ca Roland Kuhn National Research Council of Canada 1200 Montreal Road Ottawa, ON, K1A 0R6 roland.kuhn@nrc.gc.ca Aidan Pine National Research Council of Canada 5071 West Saanich Road Victoria, BC, V9E 2E7 aidan.pine@nrc.gc.ca Antti Arppe University of Alberta 4-32 Assiniboia Hall Edmonton, AB, T6G 2E7 arppe@ualberta.ca Christopher Cox Carleton University 1125 Colonel By Drive Ottawa, ON, K1S 5B6 christopher.cox@carleton.ca Marie-Odile Junker Carleton University 1125 Colonel By Drive Ottawa, ON, K1S 5B6 MarieOdile.Junker@carleton.ca Abstract In this article, we discuss which text, speech, and image technologies have been developed, and would be feasible to develop, for the approximately 60 Indigenous languages spoken in Canada. In particular, we concentrate on technologies that may be feasible to develop for most or all of these languages, not just those that may be feasible for the few most-resourced of these. We as- sess past achievements and consider future horizons for Indigenous language transliteration, text prediction, spell-checking, approximate search, machine translation, speech recognition, speaker diarization, speech synthesis, optical character recognition, and computer-aided language learn- ing. 1 Introduction There are approximately 60 Indigenous1 languages from 10 distinct language families (Rice, 2008) cur- rently spoken in Canada. Several of these languages have tens of thousands of speakers and are still acquired by most children, whereas others have a few tens or hundreds of mostly-elderly speakers; in all, 260,550 report speaking an Indigenous language at at least a conversational level (Statistics Canada, 2016). All of these languages are under significant pressure from English and French, but also have many young people interested in learning. The resurgent strength of community-driven Indigenous lin- guistic and cultural reclamation in Canada is at the heart of the growing demand for Indigenous language courses, materials and technology. Indigenous languages are of paramount importance to the nations that speak them and the benefits associated with their use are wide-ranging (Whalen et al., 2016; Reyhner, 2010; Oster et al., 2014; Marmion et al., 2014). As a specific example, research in psychology has shown a compelling correlation c⃝ Her Majesty the Queen in Right of Canada, 2018. 1In this document, “Indigenous languages” will specifically refer to Indigenous languages spoken in Canada. 2621 between Indigenous language use and a decrease in youth suicide rates on reserves in British Columbia (Chandler, 1998; Hallett et al., 2007). With increased awareness of these benefits has come increased interest by both Indigenous communities and federal and provincial governments in language technology development, to promote the revitalization and documentation of these languages. However, the development of Indigenous language technologies faces many challenges: most of these languages are highly morphologically complex, there is relatively little text and speech data available, and there can be significant differences in …

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AbstractIn this article, we discuss which text, speech, and image technologies have been developed, and would be feasible to develop, for the approximately 60 Indigenous languages spoken in Canada. In particular, we concentrate on technologies that may be feasible to develop for most or all of these languages, not just those that may be feasible for the few most-resourced of these. We assess past achievements and consider future horizons for Indigenous language transliteration, text prediction, spell-checking, approximate search, machine translation, speech recognition, speaker diarization, speech synthesis, optical character recognition, and computer-aided language learning.

Publication Details

Paper ID:
5302
Year:
2018
Publication:
TIPSTER
Publication Type:
conf
DOI:
nan