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Communication Dans Un Congrès Année : 2020

Chunk Different Kind of Spoken Discourse: Challenges for Machine Learning

Mariame Maarouf
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Flora Badin
Marie Skrovec
Isabelle Tellier

Résumé

This paper describes the development of a chunker for spoken data by supervised machine learning using the CRFs, based on a small reference corpus composed of two kinds of discourse: prepared monologue vs. spontaneous talk in interaction. The methodology considers the specific character of the spoken data. The machine learning uses the results of several available taggers, without correcting the results manually. Experiments show that the discourse type (monologue vs. free talk), the speech nature (spontaneous vs. prepared) and the corpus size can influence the results of the machine learning process and must be considered while interpreting the results.
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Dates et versions

hal-03482181 , version 1 (16-12-2021)

Identifiants

  • HAL Id : hal-03482181 , version 1

Citer

Iris Eshkol-Taravella, Mariame Maarouf, Flora Badin, Marie Skrovec, Isabelle Tellier. Chunk Different Kind of Spoken Discourse: Challenges for Machine Learning. Language Resources and Evaluation Conference, May 2020, Marseille, France. pp.5164-5168. ⟨hal-03482181⟩
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