Yanis Labrak

Yanis Labrak

Postdoctoral Researcher

Idiap Research Institute

Switzerland 🇨🇭

💼 I am a Postdoctoral Researcher at the Idiap Research Institute (Switzerland), specializing in Speech and Natural Language Processing (NLP). I previously completed my PhD at the Avignon University CS Research Lab (LIA) in collaboration with Zenidoc.

🔬 My research focuses on advanced Machine Learning, specifically Large Language Models (LLMs) and Speech Recognition tailored for complex, domain-specific applications like Healthcare.

🔭 Currently, I am investigating the multimodal integration of speech into textual LLMs. My goal is to leverage massive textual knowledge to enable seamless End-to-End performance, replacing traditional cascaded systems with more robust, unified architectures.

Spaces on HuggingFace

Models on HuggingFace

Connect with me 😃

Yanis Labrak Linkedin
Interests
  • Speech processing
  • Multi-modality (speech-text)
  • Autoregressive modeling
  • Synthetic data generation
  • Healthcare domains
Education
  • PhD in Computer Science, 2025

    Avignon University

  • MSc in Computer Science - Software Engineering, 2022

    Avignon University

  • BSc in Computer Science - Software Engineering, 2020

    Avignon University

Recent Publications

SDialog: A Python Toolkit for End-to-End Agent Building, User Simulation, Dialog Generation, and Evaluation.

EACL 2026 Paper

Language Models at the Crossroads of Text and Speech for Healthcare Applications.

Ph.D. Thesis, Université d'Avignon

Late Fusion and Multi-Level Fission Amplify Cross-Modal Transfer in Text-Speech LMs.

ArXiv 2025 Paper

An Empirical Analysis of Discrete Unit Representations in Speech Language Modeling Pre-training.

TSD 2025 Paper

Detecting Synthetic Lyrics with Few-Shot Inference.

TrustNLP @ NAACL 2025 Paper

Zero-Shot End-To-End Spoken Question Answering In Medical Domain.

InterSpeech 2024 Paper Code HuggingFace

BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains

ACL 2024 Paper Code HuggingFace

DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain.

LREC-COLING 2024 Paper Code HuggingFace

A Zero-shot and Few-shot Study of Instruction-Finetuned Large Language Models Applied to Clinical and Biomedical Tasks.

LREC-COLING 2024 Paper

How Important Is Tokenization in French Medical Masked Language Models?

LREC-COLING 2024 Paper Code HuggingFace

DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical domains.

ACL 2023 Honorable Mention Paper Code HuggingFace

BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing

NeurIPS 2022 - Datasets & Benchmarks Paper Code HuggingFace

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

ArXiv 2022 Paper HuggingFace

FrenchMedMCQA: A French Multiple-Choice Question Answering Dataset for Medical domain.

LOUHI @ EMNLP 2022 Paper Code

Experience

 
 
 
 
 
Postdoctoral Researcher
Jan 2026 – Present Martigny, Switzerland
  • Member of the Speech & Audio Processing group under the supervision of Petr Motlicek.
  • Researching the transition "From Bias to Fairness" to build the next generation of Trustworthy AI systems.
  • Developing robust speech and language models with a focus on ethical AI, bias mitigation, and transparency in large-scale multimodal systems.
  • Focus Areas: Trustworthy AI, Speech Processing, Multimodal LLMs, Fairness & Ethics.
 
 
 
 
 
Deezer Research
Research Intern
March 2024 – Sept 2024 Paris, France
  • Subject of research : AI Lyrics Detection
  • Applied Research on AI generated lyrics detection for filtering daily ingested tracks and identifying fraudulent content.
  • Explore the capabilities of lyrics based text embeddings to guide content recommendation in production.
  • Tech Stack: Docker, Python, Pytorch, Google Cloud Platform, BigQuery, Kafka, CUDA, Flask, SQL.
 
 
 
 
 
Visiting Researcher
June 2025 – August 2025 Brno, Czechia
  • Member of the JSALT 2025 "Play your Part" team.
  • Collaborated on Synthetic Dialog Generation and Analysis using LLMs.
  • Contributed to the open-source development of sdialog.
 
 
 
 
 
Avignon University
PhD Student
Aug 2022 – Sept 2025 Avignon, France
  • Thesis title: Language Models at the Crossroads of Text and Speech for Healthcare Applications
  • Organizer of the 2023 edition of the French NLP shared task DEFT (DÉfi Fouille de Textes) in Paris. The shared task was articulated around our medical multiple-choice question answering dataset FrenchMedMCQA and brought together 6 academic and industrial teams for a total of 34 participants.
  • Major success of the release of our open-source models (up to more than >110k downloads/month, multiple industry applications).
  • Presented my research in person to the French National Research Agency (my research is core to the MALADES project.
  • My work was featured in multiple news articles and a wide range of podcasts, I gave 3 interviews (CNRS, l’usine digitale and ActuIA).
  • Teachings: Parallel Programming for MSc 1st year students (c, c++, cuda), End-to-end Software Development for MSc 1st year students (python, flask, dart, flutter, JavaScript, nodejs, tesseract-ocr) and Web & Database Architecture for BSc 2nd year students (php, javascript, jQuery, css).
 
 
 
 
 
Avignon University
Research Assistant
Aug 2020 – Sept 2022 Avignon, France
  • De-identification of electronic health record using deep neural network
  • Automatic Named Entity Recognition (NER) for medical records structuration and posologic entities extraction
  • Recommendation system for ICD-10 and CCAM codification based on the patient’s medical record (operative report, anesthesia report)
  • Introducing Part-of-speech tagging into an E2E ASR via a dual decoding to reduce semantic and grammatical errors in medical transcriptions.
 
 
 
 
 
Zenidoc
Senior Research Scientist
Sep 2020 – Sep 2025 Marseille, France
  • Collect industry partners needs and study the technical feasibility of projects
  • Manage the technical deployment of solutions developed in academia
  • Promote state-of-the-art technologies and find out new applications
  • Transfer of technical knowledge to technical teams
  • Supervise annotations phases for named-entity-recognition, part-of-speech tagging and documents classification
  • Manage in-house technological benchmarking comparison