Javier Vera


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CLD² Language Documentation Meets Natural Language Processing for Revitalising Endangered Languages
Roberto Zariquiey | Arturo Oncevay | Javier Vera
Proceedings of the Fifth Workshop on the Use of Computational Methods in the Study of Endangered Languages

Language revitalisation should not be understood as a direct outcome of language documentation, which is mainly focused on the creation of language repositories. Natural language processing (NLP) offers the potential to complement and exploit these repositories through the development of language technologies that may contribute to improving the vitality status of endangered languages. In this paper, we discuss the current state of the interaction between language documentation and computational linguistics, present a diagnosis of how the outputs of recent documentation projects for endangered languages are underutilised for the NLP community, and discuss how the situation could change from both the documentary linguistics and NLP perspectives. All this is introduced as a bridging paradigm dubbed as Computational Language Documentation and Development (CLD²). CLD² calls for (1) the inclusion of NLP-friendly annotated data as a deliverable of future language documentation projects; and (2) the exploitation of language documentation databases by the NLP community to promote the computerization of endangered languages, as one way to contribute to their revitalization.

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Building an Endangered Language Resource in the Classroom: Universal Dependencies for Kakataibo
Roberto Zariquiey | Claudia Alvarado | Ximena Echevarría | Luisa Gomez | Rosa Gonzales | Mariana Illescas | Sabina Oporto | Frederic Blum | Arturo Oncevay | Javier Vera
Proceedings of the Thirteenth Language Resources and Evaluation Conference

In this paper, we launch a new Universal Dependencies treebank for an endangered language from Amazonia: Kakataibo, a Panoan language spoken in Peru. We first discuss the collaborative methodology implemented, which proved effective to create a treebank in the context of a Computational Linguistic course for undergraduates. Then, we describe the general details of the treebank and the language-specific considerations implemented for the proposed annotation. We finally conduct some experiments on part-of-speech tagging and syntactic dependency parsing. We focus on monolingual and transfer learning settings, where we study the impact of a Shipibo-Konibo treebank, another Panoan language resource.