This paper gives an overview of the Cardamom project, which aims to close the resource gap for minority and under-resourced languages by means of deep-learning-based natural language processing (NLP) and exploiting similarities of closely-related languages. The project further extends this idea to historical languages, which can be considered as closely related to their modern form, and as such aims to provide NLP through both space and time for languages that have been ignored by current approaches.
Mccrae, J. P., Fransen, T., Cardamom: Comparative Deep Models for Minority and Historical Languages, Contributed paper, in Proceedings of the 1st International Conference on Language Technologies for All, (Paris, France, 05-06 December 2019), European Language Resources Association (ELRA), Paris, France 2019: 276-279 [https://hdl.handle.net/10807/270149]
Cardamom: Comparative Deep Models for Minority and Historical Languages
Fransen, Theodorus
2019
Abstract
This paper gives an overview of the Cardamom project, which aims to close the resource gap for minority and under-resourced languages by means of deep-learning-based natural language processing (NLP) and exploiting similarities of closely-related languages. The project further extends this idea to historical languages, which can be considered as closely related to their modern form, and as such aims to provide NLP through both space and time for languages that have been ignored by current approaches.
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