Jean-Luc Rouas

746 total citations
41 papers, 257 citations indexed

About

Jean-Luc Rouas is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Signal Processing. According to data from OpenAlex, Jean-Luc Rouas has authored 41 papers receiving a total of 257 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 21 papers in Experimental and Cognitive Psychology and 16 papers in Signal Processing. Recurrent topics in Jean-Luc Rouas's work include Speech Recognition and Synthesis (23 papers), Music and Audio Processing (13 papers) and Speech and Audio Processing (11 papers). Jean-Luc Rouas is often cited by papers focused on Speech Recognition and Synthesis (23 papers), Music and Audio Processing (13 papers) and Speech and Audio Processing (11 papers). Jean-Luc Rouas collaborates with scholars based in France, Luxembourg and Portugal. Jean-Luc Rouas's co-authors include Jérôme Farinas, François Pellegrino, Régine Andre-Obrecht, Julien Pinquier, Vincent Martin, Pierre Philip, Jean‐Arthur Micoulaud‐Franchi, Régis Lopez, Yves Dauvilliers and Isabel Trancoso and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sleep Medicine Reviews and Frontiers in Psychiatry.

In The Last Decade

Jean-Luc Rouas

35 papers receiving 238 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jean-Luc Rouas France 9 157 138 117 40 27 41 257
Bela Usabaev Germany 5 200 1.3× 142 1.0× 80 0.7× 38 0.9× 25 0.9× 7 329
Éva Székely Sweden 11 285 1.8× 130 0.9× 70 0.6× 21 0.5× 14 0.5× 51 361
Taniya Mishra United States 11 217 1.4× 108 0.8× 122 1.0× 34 0.8× 7 0.3× 31 291
Jochen Weiner Germany 9 225 1.4× 71 0.5× 67 0.6× 46 1.1× 34 1.3× 17 332
Slim Ouni France 11 177 1.1× 203 1.5× 192 1.6× 46 1.1× 28 1.0× 51 370
Sheri Hunnicutt Sweden 12 245 1.6× 85 0.6× 103 0.9× 30 0.8× 47 1.7× 35 348
Wojciech Majewski Poland 9 153 1.0× 97 0.7× 130 1.1× 36 0.9× 34 1.3× 22 264
Claire Pillot-Loiseau France 8 84 0.5× 51 0.4× 96 0.8× 17 0.4× 61 2.3× 41 202
Prashanth Gurunath Shivakumar United States 7 131 0.8× 102 0.7× 96 0.8× 44 1.1× 16 0.6× 18 241
Finnian Kelly Ireland 10 202 1.3× 167 1.2× 19 0.2× 23 0.6× 21 0.8× 33 284

Countries citing papers authored by Jean-Luc Rouas

Since Specialization
Citations

This map shows the geographic impact of Jean-Luc Rouas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jean-Luc Rouas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean-Luc Rouas more than expected).

Fields of papers citing papers by Jean-Luc Rouas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Luc Rouas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jean-Luc Rouas. The network helps show where Jean-Luc Rouas may publish in the future.

Co-authorship network of co-authors of Jean-Luc Rouas

This figure shows the co-authorship network connecting the top 25 collaborators of Jean-Luc Rouas. A scholar is included among the top collaborators of Jean-Luc Rouas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jean-Luc Rouas. Jean-Luc Rouas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Rouas, Jean-Luc, et al.. (2024). Usefulness of Emotional Prosody in Neural Machine Translation. SPIRE - Sciences Po Institutional REpository. 1230–1234.
3.
Rouas, Jean-Luc, et al.. (2024). Conditioning LLMs with Emotion in Neural Machine Translation. 33–38.
4.
Martin, Vincent & Jean-Luc Rouas. (2024). Estimating Symptoms and Clinical Signs Instead of Disorders: The Path Toward The Clinical Use of Voice and Speech Biomarkers In Psychiatry. SPIRE - Sciences Po Institutional REpository. 10606–10610. 2 indexed citations
5.
Martin, Vincent, et al.. (2023). Automatic detection of schwa in French hypersomniac patients. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
6.
Rouas, Jean-Luc, et al.. (2023). Variable Scale Pruning for Transformer Model Compression in End-to-End Speech Recognition. Algorithms. 16(9). 398–398. 2 indexed citations
7.
Martin, Vincent, et al.. (2023). “Prediction of Sleepiness Ratings from Voice by Man and Machine”: A Perceptual Experiment Replication Study. SPIRE - Sciences Po Institutional REpository. 1–5.
8.
Rouas, Jean-Luc, et al.. (2022). Fine-grained analysis of the transformer model for efficient pruning. SPIRE - Sciences Po Institutional REpository. 897–902. 2 indexed citations
9.
Martin, Vincent, Jean-Luc Rouas, Pierre Philip, et al.. (2022). How Does Comparison With Artificial Intelligence Shed Light on the Way Clinicians Reason? A Cross-Talk Perspective. Frontiers in Psychiatry. 13. 926286–926286. 8 indexed citations
10.
Fourer, Dominique, et al.. (2022). Speech Emotion Recognition using Time-frequency Random Circular Shift and Deep Neural Networks. HAL (Le Centre pour la Communication Scientifique Directe). 585–589. 2 indexed citations
11.
Martin, Vincent, Régis Lopez, Yves Dauvilliers, et al.. (2022). Sleepiness in adults: An umbrella review of a complex construct. Sleep Medicine Reviews. 67. 101718–101718. 19 indexed citations
12.
Martin, Vincent, et al.. (2022). Does sleepiness influence reading pauses in hypersomniac patients?. HAL (Le Centre pour la Communication Scientifique Directe). 62–66. 2 indexed citations
13.
Martin, Vincent, Jean-Luc Rouas, Jean‐Arthur Micoulaud‐Franchi, Pierre Philip, & Jarek Krajewski. (2021). How to Design a Relevant Corpus for Sleepiness Detection Through Voice?. Frontiers in Digital Health. 3. 686068–686068. 7 indexed citations
14.
Rouas, Jean-Luc, et al.. (2019). End-to-End Speech Recognition: A review for the French Language. arXiv (Cornell University). 6 indexed citations
15.
Mareüil, Philippe Boula de, et al.. (2011). In search of cues discriminating West-african accents in French. HAL (Le Centre pour la Communication Scientifique Directe). 725–728. 1 indexed citations
16.
Rouas, Jean-Luc, et al.. (2010). Comparaison des propriétés acoustiques de la parole lue, préparée et conversationnelle en français. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
17.
Rouas, Jean-Luc, et al.. (2008). Portuguese variety identification on broadcast news. Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. 11. 4229–4232. 1 indexed citations
18.
Farinas, Jérôme, Dominique Fohr, Irina Illina, et al.. (2003). Audio Indexing on the Web: a Preliminary Study of Some Audio Descriptors. 3 indexed citations
19.
Rouas, Jean-Luc, Jérôme Farinas, François Pellegrino, & Régine Andre-Obrecht. (2003). Modeling prosody for language identification on read and spontaneous speech. 11. I–753. 2 indexed citations
20.
Rouas, Jean-Luc, et al.. (2003). Modeling prosody for language identification on read and spontaneous speech. 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).. I–40. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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