This paper describes the expansion of a finite state transducer (FST) for the transitive verb system of Tsuut’ina (ISO 639-3: srs), a Dene (Athabaskan) language spoken in Alberta, Canada. Dene languages have unique templatic morphology, in which lexical, inflectional and derivational tiers are interlaced. Drawing on data from close to 9,000 verbal forms, the expanded model can handle a great range of common and rare argument structure types, including ditransitive and uniquely Dene object experiencer verbs. While challenges of speed remain, this expansion shows the ability of FST modelling to handle morphology of this type, and the expnded FST shows great promise for community language applications such as a morphologically informed online dictionary and word predictor, and for further FST development. This paper describes the expansion of a finite state transducer (FST) for the transitive verb system of Tsuut’ina (ISO 639-3: srs), a Dene (Athabaskan) language spoken in Alberta, Canada. Dene languages have unique templatic morphology, in which lexical, inflectional and derivational tiers are interlaced. Drawing on data from over 12,000 verbs forms, the expanded model can handle a great range of common and rare argument structure types, including ditransitive and uniquely Dene object experiencer verbs. While challenges of speed remain, this expansion shows the ability of FST modelling to handle morphology of this type, and the expnded FST shows great promise for community language applications such as a morphologically informed online dictionary and word predictor, and for further FST development.

Roland Kuhn, Fineen Davis, Alain Désilets, Eric Joanis, Anna Kazantseva, Rebecca Knowles, Patrick Littell, Delaney Lothian, Aidan Pine, Caroline Running Wolf, Eddie Santos, Darlene Stewart, Gilles Boulianne, Vishwa Gupta, Brian Maracle Owennatékha, Akwiratékha’ Martin, Christopher Cox, Marie-Odile Junker, Olivia Sammons, Delasie Torkornoo, Nathan Thanyehténhas Brinklow, Sara Child, Benoît Farley, David Huggins-Daines, Daisy Rosenblum, Heather Souter. Proceedings of the 28th International Conference on Computational Linguistics. 2020.

In this paper, we present a fractional version of Haemers' bound on the Shannon capacity of a graph, which is originally due to Blasiak. This bound is a common strengthening of both Haemers' bound and the fractional chromatic number of a graph. We show that this fractional version outperforms any bound on the Shannon capacity that could be attained through Haemers' bound. We show also that this bound is multiplicative, unlike Haemers' bound.

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 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.