Towards High-Quality LLM-Based Data for French Spontaneous Speech Simplification: an Exo-Refinement Approach

Authors

Institutions

Publication Details

Published
2025-08-17
DOI
https://doi.org/10.21437/interspeech.2025-452
Primary Topic
Text Readability and Simplification
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Towards High-Quality LLM-Based Data for French Spontaneous Speech Simplification: an Exo-Refinement Approach

Didier Schwab, Lucia Ormaechea-Grijalba, Pierrette Bouillon, Nikolaos Tsourakis et al.
Text Readability and Simplification
article

Towards High-Quality LLM-Based Data for French Spontaneous Speech Simplification: an Exo-Refinement Approach

Didier Schwab, Lucia Ormaechea-Grijalba, Pierrette Bouillon, Nikolaos Tsourakis, Benjamin Lecouteux
article en

Abstract

No abstract available for this paper.
University of Geneva (CH), Laboratoire d'Informatique de Grenoble (FR), GIPSA-Lab (FR), Université Grenoble Alpes (FR)
National Science Foundation, Agence Nationale de la Recherche, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Openalex Percentile: Top 84%
Text Readability and Simplification
DOIOpen Access PDFOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.