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Celux, G. and Clairambault, J. (1992) Estimation Markov Hidden Chains: Problems and Methods. CNRS, Thematic Days on Markovian Approaches on Images and Signal, September.

has been cited by the following article:

• TITLE: Morpho-Syntactic Tagging of Text in “Baoule” Language Based on Hidden Markov Models (HMM)

  AUTHORS: Hyacinthe Konan, Bi Tra Gooré, Raymond Gbégbé, Olivier Asseu

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

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.9 No.10, October 25, 2016

  ABSTRACT: 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.