Author(s)

Hyacinthe Konan¹, Bi Tra Gooré², Raymond Gbégbé², Olivier Asseu^1,2

¹Ecole Supérieure Africaine des TICs (ESATIC), Abidjan, Côte d’Ivoire.
²Institut National Polytechnique Félix Houphouët Boigny (INP-HB), Yamoussoukro, Côte d’Ivoire.

The label text is a very important tool for the automatic processing of language. It is used in several applications such as morphological and syntactic text analysis, index-ing, retrieval, finished networks deterministic (in which all combinations of words that are accepted by the grammar are listed) or by statistical grammars (e.g., an n-gram in which the probabilities of sequences of n words in a specific order are given), etc. In this article, we developed a morphosyntactic labeling system language “Baoule” using hidden Markov models. This will allow us to build a tagged reference corpus and rep-resent major grammatical rules faced “Baoule” language in general. To estimate the parameters of this model, we used a training corpus manually labeled using a set of morpho-syntactic labels. We then proceed to an improvement of the system through the re-estimation procedure parameters of this model.

Corpus, the Set of Tags, the Morpho-Syntactic Tagging, “Baoule” Language, Hidden Markov Model

Konan, H. , Gooré, B. , Gbégbé, R. and Asseu, O. (2016) Morpho-Syntactic Tagging of Text in “Baoule” Language Based on Hidden Markov Models (HMM). Journal of Software Engineering and Applications, 9, 516-523. doi: 10.4236/jsea.2016.910034.