Lexical and Grammar Resource Engineering for Runyankore & Rukiga: A Symbolic Approach

Current research in computational linguistics and natural language processing (NLP) requires the existence of language resources. Whereas these resources are available for a few well-resourced languages, there are many languages that have been neglected. Among the neglected and / or under-resourced languages are Runyankore and Rukiga (henceforth referred to as Ry/Rk). Recently, the NLP community has started to acknowledge that resources for under-resourced languages should also be given priority. Why? One reason being that as far as language typology is concerned, the few well-resourced languages do not represent the structural diversity of the remaining languages. The central focus of this thesis is about enabling the computational analysis and generation of utterances in Ry/Rk. Ry/Rk are two closely related languages spoken by about 3.4 and 2.4 million people respectively. They belong to the Nyoro-Ganda (JE10) language zone of the Great Lakes, Narrow Bantu of the Niger-Congo language family.The computational processing of these languages is achieved by formalising the grammars of these two languages using Grammatical Framework (GF) and its Resource Grammar Library (RGL). In addition to the grammar, a general-purpose computational lexicon for the two languages is developed. Although we utilise the lexicon to tremendously increase the lexical coverage of the grammars, the lexicon can be used for other NLP tasks.In this thesis a symbolic / rule-based approach is taken because the lack of adequate languages resources makes the use of data-driven NLP approaches unsuitable for these languages

Towards a Resource Grammar for Runyankore and Rukiga

Currently, there is a lack of computational grammar resources for many under-resourced languages which limits the ability to develop Natural Language Processing (NLP) tools and applications such as Multilingual Document Authoring, Computer-Assisted Language Learning (CALL) and Low-Coverage Machine Translation (MT) for these languages. In this paper, we present our attempt to formalise the grammar of two such languages: Runyankore and Rukiga. For this formalisation we use the Grammatical Framework (GF) and its Resource Grammar Library (GF-RGL)

Towards computational resource grammars for runyankore and rukiga

In this paper, we present computational resource grammars of Runyankore and Rukiga (R&R) languages. Runyankore and Rukiga are two under-resourced Bantu Languages spoken by about 6 million people indigenous to South Western Uganda, East Africa. We used Grammatical Framework (GF), a multilingual grammar formalism and a special-purpose functional programming language to formalise the descriptive grammar of these languages. To the best of our knowledge, these computational resource grammars are the first attempt to the creation of language resources for R&R. In Future Work, we plan to use these grammars to bootstrap the generation of other linguistic resources such as multilingual corpora that make use of data-driven approaches to natural language processing feasible. In the meantime, they can be used to build Computer-Assisted Language Learning (CALL) applications for these languages among others