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Materials for the study: Exploring Machine Learning perspectives for electroglottographic signals

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EGG-ML:

This repository hosts the project "Exploring Machine Learning Perspectives for Electroglottographic Signal Analysis." It currently includes two projects:

  1. The First Attempt (2022)
    Conducted at LIG (Laboratoire d’Informatique de Grenoble - UMR 5217), this project was carried out under the joint supervision of Solange Rossato and Maximin Coavoux. The materials for this project are available in the CLD2025_EGG directory.

  2. The Second Attempt (Ongoing) Currently being conducted at LLF (Laboratoire de Linguistique Formelle – UMR 7110), this project is supervised by Guillaume Winiewski and supported by Alexis Michaud1 . This collaboration seeks to bridge the gap between field linguists and computer engineers, accelerating and simplifying the archiving and study of endangered languages. The materials for this ongoing effort are available in the InputData_tsv directory.

Footnotes

  1. Leur travail commun vise à utiliser la puissance de calcul informatique pour mieux comprendre la structure de langues peu analysées et souvent en danger. More about this initiative can be learned through a VOX podcast: podcast.ausha.co/vox-podcast-labex-efl/unir-informatique-et-linguistique

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