@Book{W18-48:2018,
  editor    = {Judith L. Klavans},
  title     = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  url       = {http://www.aclweb.org/anthology/W18-48}
}

@InProceedings{klavans:2018:W18-48,
  author    = {Klavans, Judith},
  title     = {Computational Challenges for Polysynthetic Languages},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {1--11},
  abstract  = {Given advances in computational linguistic analysis of complex languages using Machine Learning as well as standard Finite State Transducers, coupled with recent efforts in language revitalization, the time was right to organize a first workshop to bring together experts in language technology and linguists on the one hand with language practitioners and revitalization experts on the other. This one-day meeting provides a promising forum to discuss new research on polysynthetic languages in combination with the needs of linguistic communities where such languages are written and spoken.},
  url       = {http://www.aclweb.org/anthology/W18-4801}
}

@InProceedings{moeller-EtAl:2018:W18-48,
  author    = {Moeller, Sarah  and  Kazeminejad, Ghazaleh  and  Cowell, Andrew  and  Hulden, Mans},
  title     = {A Neural Morphological Analyzer for Arapaho Verbs Learned from a Finite State Transducer},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {12--20},
  abstract  = {We experiment with training an encoder-decoder neural model for mimicking the behavior of an existing hand-written finite-state morphological grammar for Arapaho verbs, a polysynthetic language with a highly complex verbal inflection system. After adjusting for ambiguous parses, we find that the system is able to generalize to unseen forms with accuracies of 98.68% (unambiguous verbs) and 92.90% (all verbs).},
  url       = {http://www.aclweb.org/anthology/W18-4802}
}

@InProceedings{littell:2018:W18-48,
  author    = {Littell, Patrick},
  title     = {Finite-state morphology for Kwak'wala: A phonological approach},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {21--30},
  abstract  = {This paper presents the phonological layer of a Kwak'wala finite-state morphological transducer, using the phonological hypotheses of Lincoln and Rath (1986) and the lenient composition operation of Karttunen (1998) to mediate the complicated relationship between underlying and surface forms. The resulting system decomposes the wide variety of surface forms in such a way that the morphological layer can be specified using unique and largely concatenative morphemes.},
  url       = {http://www.aclweb.org/anthology/W18-4803}
}

@InProceedings{andriyanets-tyers:2018:W18-48,
  author    = {Andriyanets, Vasilisa  and  Tyers, Francis},
  title     = {A prototype finite-state morphological analyser for Chukchi},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {31--40},
  abstract  = {In this article we describe the application of finite-state transducers to the morphological and phonological systems of Chukchi,},
  url       = {http://www.aclweb.org/anthology/W18-4804}
}

@InProceedings{lessard-brinklow-levison:2018:W18-48,
  author    = {Lessard, Greg  and  Brinklow, Nathan  and  Levison, Michael},
  title     = {Natural Language Generation for Polysynthetic Languages: Language Teaching and Learning Software for Kanyen’kéha (Mohawk)},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {41--52},
  abstract  = {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.},
  url       = {http://www.aclweb.org/anthology/W18-4805}
}

@InProceedings{kazantseva-EtAl:2018:W18-48,
  author    = {Kazantseva, Anna  and  Maracle, Owennatekha Brian  and  Maracle, Ronkwe’tiyóhstha Josiah  and  Pine, Aidan},
  title     = {Kawennón:nis: the Wordmaker for Kanyen'kéha},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {53--64},
  abstract  = {In this paper we describe preliminary work on Kawennón:nis, a verb conjugator for Kanyen'kéha (Ohsweken dialect). The project is the result of a collaboration between Onkwawenna Kentyohkwa Kanyen'kéha immersion school and the Canadian National Research Council's Indigenous Language Technology lab. The purpose of Kawennón:nis is to build on the educational successes of the Onkwawenna Kentyohkwa school and develop a tool that assists students in learning how to conjugate verbs in Kanyen'kéha; a skill that is essential to mastering the language. Kawennón:nis is implemented with both web and mobile front-ends that communicate with an application programming interface that in turn communicates with a symbolic language model implemented as a finite state transducer. Eventually, it will serve as a foundation for several other applications for both Kanyen'kéha and other Iroquoian languages.},
  url       = {http://www.aclweb.org/anthology/W18-4806}
}

@InProceedings{micher:2018:W18-48,
  author    = {Micher, Jeffrey},
  title     = {Using the Nunavut Hansard Data for Experiments in Morphological Analysis and Machine Translation},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {65--72},
  abstract  = {Inuktitut is a polysynthetic language spoken in Northern Canada and is one of the official languages of the Canadian territory of Nunavut. As such, the Nunavut Legislature publishes all of its proceedings in parallel English and Inuktitut. Several parallel English-Inuktitut corpora from these proceedings have been created from these data and are publically available. The corpus used for current experiments is described. Morphological processing of one of these corpora was carried out and details about the processing are provided. Then, the processed corpus was used in morphological analysis and machine translation (MT) experiments. The morphological analysis experiments aimed to improve the coverage of morphological processing of the corpus, and compare an additional experimental condition to previously published results. The machine translation experiments made use of the additional morphologically analyzed word types in a statistical machine translation system designed to translate to and from Inuktitut morphemes. Results are reported and next steps are defined.},
  url       = {http://www.aclweb.org/anthology/W18-4807}
}

@InProceedings{mager-EtAl:2018:W18-48,
  author    = {Mager, Manuel  and  Mager, Elisabeth  and  Medina-Urrea, Alfonso  and  Meza Ruiz, Ivan Vladimir  and  Kann, Katharina},
  title     = {Lost in Translation: Analysis of Information Loss During Machine Translation Between Polysynthetic and Fusional Languages},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {73--83},
  abstract  = {Machine translation from polysynthetic to fusional languages is a challenging task, which gets further complicated by the limited amount of parallel text available. },
  url       = {http://www.aclweb.org/anthology/W18-4808}
}

@InProceedings{moeller-hulden:2018:W18-48,
  author    = {Moeller, Sarah  and  Hulden, Mans},
  title     = {Automatic Glossing in a Low-Resource Setting for Language Documentation},
  booktitle = {Proceedings of the Workshop on Computational Modeling of Polysynthetic Languages},
  month     = {August},
  year      = {2018},
  address   = {Santa Fe, New Mexico, USA},
  publisher = {Association for Computational Linguistics},
  pages     = {84--93},
  abstract  = {Morphological analysis of morphologically rich and low-resource languages is important to both descriptive linguistics and natural language processing. Field documentary efforts usually procure analyzed data in cooperation with native speakers who are capable of providing some level of linguistic information. Manually annotating such data is very expensive and the traditional process is arguably too slow in the face of language endangerment and loss. We report on a case study of learning to automatically gloss a Nakh-Daghestanian language, Lezgi, from a very small amount of seed data. We compare a conditional random field based sequence labeler and a neural encoder-decoder model and show that a nearly 0.9 F1-score on labeled accuracy of morphemes can be achieved with 3,000 words of transcribed oral text. Errors are mostly limited to morphemes with high allomorphy. These results are potentially useful for developing rapid annotation and fieldwork tools to support documentation of morphologically rich, endangered languages.},
  url       = {http://www.aclweb.org/anthology/W18-4809}
}