Lucía Ormaechea


2024

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Simplification Strategies in French Spontaneous Speech
Lucía Ormaechea | Nikos Tsourakis | Didier Schwab | Pierrette Bouillon | Benjamin Lecouteux
Proceedings of the Workshop on DeTermIt! Evaluating Text Difficulty in a Multilingual Context @ LREC-COLING 2024

Automatic Text Simplification (ATS) aims at rewriting texts into simpler variants while preserving their original meaning, so they can be more easily understood by different audiences. While ATS has been widely used for written texts, its application to spoken language remains unexplored, even if it is not exempt from difficulty. This study aims to characterize the edit operations performed in order to simplify French transcripts for non-native speakers. To do so, we relied on a data sample randomly extracted from the Orféo-CEFC French spontaneous speech dataset. In the absence of guidelines to direct this process, we adopted an intuitive simplification approach, so as to investigate the crafted simplifications based on expert linguists’ criteria, and to compare them with those produced by a generative AI (namely, ChatGPT). The results, analyzed quantitatively and qualitatively, reveal that the most common edits are deletions, and affect oral production aspects, like restarts or hesitations. Consequently, candidate simplifications are typically register-standardized sentences that solely include the propositional content of the input. The study also examines the alignment between human- and machine-based simplifications, revealing a moderate level of agreement, and highlighting the subjective nature of the task. The findings contribute to understanding the intricacies of simplifying spontaneous spoken language. In addition, the provision of a small-scale parallel dataset derived from such expert simplifications, Propicto-Orféo-Simple, can facilitate the evaluation of speech simplification solutions.

2023

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PROPICTO: Developing Speech-to-Pictograph Translation Systems to Enhance Communication Accessibility
Lucía Ormaechea | Pierrette Bouillon | Maximin Coavoux | Emmanuelle Esperança-Rodier | Johanna Gerlach | Jerôme Goulian | Benjamin Lecouteux | Cécile Macaire | Jonathan Mutal | Magali Norré | Adrien Pupier | Didier Schwab
Proceedings of the 24th Annual Conference of the European Association for Machine Translation

PROPICTO is a project funded by the French National Research Agency and the Swiss National Science Foundation, that aims at creating Speech-to-Pictograph translation systems, with a special focus on French as an input language. By developing such technologies, we intend to enhance communication access for non-French speaking patients and people with cognitive impairments.

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Simple, Simpler and Beyond: A Fine-Tuning BERT-Based Approach to Enhance Sentence Complexity Assessment for Text Simplification
Lucía Ormaechea | Nikos Tsourakis | Didier Schwab | Pierrette Bouillon | Benjamin Lecouteux
Proceedings of the 6th International Conference on Natural Language and Speech Processing (ICNLSP 2023)

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Extracting Sentence Simplification Pairs from French Comparable Corpora Using a Two-Step Filtering Method
Lucía Ormaechea | Nikos Tsourakis
Proceedings of the 8th edition of the Swiss Text Analytics Conference