Constructing Sound Zones using machine learning on a large dataset Supervsisors : Théo Mariotte (LIUM), Manuel Melon (LAUM), Marie Tahon (LIUM) Host Laboratory: Laboratoire d’Informatique de l’Université du Mans (LIUM) – Laboratoire d’Acoustique de l’Université du Mans (LAUM). Location : Le Mans Université Beginning of internship: Between January and March 2025 Contact : Théo Mariotte, […]
LST day The LST team day is being held on 17 October. On this occasion, the young and more experienced researchers present their research themes. There will also be a presentation on European projects by Hélène Dereszowski from DRIS. This year, 3 workshops will focus on the following themes: 1. Spoof diarization audiovisuel 2. […]
Corpus: Kurdish TED (KUTED)Licence: CreativeCommons Attribution NonCommercial-ShareAlike 4.0 International License.URL: https://huggingface.co/datasets/aranemini/kurdishtedAuthor(s): Mohammad MohammadaminiAntoine LaurentDescription Kurdish TED (KUTED) is the first Speech-to-Text-Translation (S2TT) dataset for the Central Kurdish language derived from TED Talks and TEDx. The corpus consists of 91,000 pairs, encompassing 170 hours of English audio, 1.65 million English tokens, and 1.40 million Central Kurdish […]
Speech Translation System – Low-resource Languages to High-resource Languages Supervisors: Aghilas Sini (LIUM), Jane Wottawa (LIUM) Hosting lab: LIUM (Laboratoire d’Informatique de l’Université du Mans) Place: Le Mans Université Beginning of internship : March 2024 Contacts: Aghilas Sini and Jane Wottawa, (firstname.name@univ-lemans.fr) Application: Send a CV, a covering letter relevant to the proposed subject, […]
Seminar from Heydi Méndez Vázquez, researcher at CENATAV Date: 09/10/2024 Time: 11h00 Place: IC2, Boardroom Speaker: Heydi Méndez Vázquez Lightweight CNNs for Face Recognition Applications Face recognition (FR) is an active research topic in computer vision and image understanding. It is one of the most used and extended biometric techniques. The […]
Optimizing Human Intervention for Synthetic Speech Quality Evaluation: Active Learning for AdaptabilityStarting: 01/10/2024PhD Student: Natacha MiniconiAdvisor(s): Anthony LarcherCo-advisor(s): Meysam ShamsiFunding: Region TandemContext: The primary objective of Text-to-Speech (TTS), speech conversion and speech to speech translation system is to synthesize or generate a high-quality speech signal. Typically, the quality of synthetic speech is subjectively evaluated by […]
Multilingual Multimodal Voice Translation – Expressive (TV2M-E)Date: 06/2024 – 06/2026Funding: Région Pays de la LoireCall: PULSARURL: https://lium.univ-lemans.fr/en/tv2m-e/LIUM Participant(s): Aghilas SiniSummary A bilingual or polyglot speaker has the ability to communicate coherently in several languages, adapting to different contexts. Transferring this skill to machines could contribute to the preservation of cultural heritage by maintaining less privileged […]
Seminar from Anthony Larcher, Professor at LIUM Date: 02/07/2024 Time: 10h00 Localization: IC2, Boardroom Speaker: Anthony Larcher Trustworthy, explainable, interpretable… what can we expect for speech processing? Improvements in the performance of automated systems have led to the widespread commercial deployment of applications that are still poorly understood. To ensure the […]
PhD defence, Thibault Prouteau Date : 03/07/2024 Time : 14h00 Location : Le Mans Université; IC2 buiding Auditorium Title: Graphs, Words, and Communities: Converging Paths to Interpretability with a Frugal Embedding Framework Jury members : Vincent LABATUT, Assistant Professor, Université d’Avignon, Reviewer Christine LARGERON, Professor, Université Jean Monnet, Saint-Étienne, Reviewer Cécile BOTHOREL, Assistant […]
Seminar from Yannick Yomie Nzeuhang, PhD student at Université Yaoundé 1 and ESPERANTO secondee at LIUM Date: 21/06/2024 Time: 14h00 Localization: IC2, Boardroom Speaker: Yannick Yomie Nzeuhang Enriching acoustic representation for for LRL(Low resources Languages) A popular approach in the literature for tackling the task of speech recognition for low-resource languages […]
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