Learning a stochastic part of speech tagger for sinhala

Jayasuriya, M. M.; Weerasinghe, A. R.

doi:10.1109/icter.2013.6761168

Cited by 7 publications

(1 citation statement)

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“…While here it is obvious that there has been some follow up work after the initial foundation, it seems, all of that has been internal to one research group at one institution as neither the data nor the tools of any of these findings have been made available for the use of external researchers. Several attempts to create a stochastic PoS tagger for Sinhala has been done with the studies by Herath and Weerasinghe [121], Jayaweera and Dias [122], and Jayasuriya and Weerasinghe [123] being the most notable. Within a single group which did one of the above stochastic studies [122], yet another set of studies was carried out to create a Sinhala PoS tagger starting with the foundation of Jayaweera and Dias [124] which then extended to a Hidden Markov Model (HMM) based approach [125] and an analysis of unknown words [126,127].…”

Section: Part Of Speech Taggersmentioning

confidence: 99%

Survey on Publicly Available Sinhala Natural Language Processing Tools and Research

Silva¹

2019

Preprint

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Sinhala is the native language of the Sinhalese people who make up the largest ethnic group of Sri Lanka. The language belongs to the globe-spanning language tree, Indo-European. However, due to poverty in both linguistic and economic capital, Sinhala, in the perspective of Natural Language Processing tools and research, remains a resource-poor language which has neither the economic drive its cousin English has nor the sheer push of the law of numbers a language such as Chinese has. A number of research groups from Sri Lanka have noticed this dearth and the resultant dire need for proper tools and research for Sinhala natural language processing. However, due to various reasons, these attempts seem to lack coordination and awareness of each other. The objective of this paper is to fill that gap of a comprehensive literature survey of the publicly available Sinhala natural language tools and research so that the researchers working in this field can better utilize contributions of their peers. As such, we shall be uploading this paper to arXiv and perpetually update it periodically to reflect the advances made in the field.

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Section: Part Of Speech Taggersmentioning

confidence: 99%