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Gaspard Michel

Gaspard Michel has 2 papers in our library, in 2026, most of them on Speech & spoken language; often with Christophe Cerisara, Elena V. Epure.

2 papers in our library · 2026

OpenAlex · h-index 2 · 19 works · 10 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1 time in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #11992

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🔬Laboratoire Lorrain de Recherche en Informatique et ses ApplicationsNancy · France2022–2026 · 14 paperscurrent🔬Idiap Research InstituteMartigny-Combe · Switzerland2025–2026 · 3 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksExperimental and Cognitive Psychology · 1 workLiterature and Literary Theory · 1 workPsychology · 1 workSignal Processing · 1 work

🧭 Topics 1Research subjects and languages the work is about.Speech & spoken language · 1 work

 Works by year

2020s

20262 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Computational Narrative Understanding for Expressive Text-to-Speech (2026)
    Audiobook corpora are often seen as too flat for training expressive text-to-speech (TTS). The authors challenge this view. They note that fiction recordings alternate between neutral narration and livelier character dialogue, and existing segmentations blend the two. On LibriHeavy-small, pitch variability increases…
  2. S-VoCAL: A Dataset and Evaluation Framework for Inferring Speaking Voice Character Attributes in Literature (2026)
    Synthetic audiobook narration still struggles to voice fictional characters convincingly. Assigning each character a fitting voice requires knowing traits like age, gender or origin, which novels often leave implicit or spread across distant chapters. Earlier character datasets mostly offer free-form literary…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Automatic Annotation of Direct Speech in Written French Narratives ↗Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetNoé Durandard et al.2023 · 2 citations
  2. Computational Narrative Understanding for Expressive Text-to-SpeechFindings of the Association for Computational LinguisticsGaspard Michel, Elena V. Epure, Christophe Cerisara2026
  3. S-VoCAL: A Dataset and Evaluation Framework for Inferring Speaking Voice Character Attributes in LiteratureLanguage Resources and Evaluation Conference (LREC)Abigail Berthe-Pardo, Gaspard Michel, Elena V. Epure, et al.2026

 Co-authors here

2 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read).

Updated

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