PhD Job Day

À propos Sanjana Sankar

  • Vous êtes Doctorant·e
  • Année 3ème année
  • Année de Master 1ère année
  • Etablissement actuel (si doctorant) Autre
  • Etablissement actuel Master (si master) Université de Lille
  • établissement dans lequel j’ai obtenu le doctorat Université de Lille
  • Si autre établissement, précisez University of Grenoble Alpes
  • Ecole doctorale Autre
  • Si autre Ecole doctorale, précisez EEATS
  • Laboratoire CNRS GIPSA Lab
  • Discipline Informatique
  • Autre discipline, si thèse pluridisciplinaire Signal processing
  • Adresse personnelle CNRS-GIPSA Lab, 11 Rue des Mathematics
  • Code postal 38400
  • Ville Saint Martin D'Heres
  • Pays France
  • Date de naissance (format JJ/MM/AAAA) 02/01/1997
  • Je comprends et accepte la politique de confidentialité Je comprends et accepte la politique de confidentialité



  • 2021 - Present
    CNRS Gipsa Lab, Univesity of Grenoble Alpes

    Doctoral Candidate (Marie Sklodowska-Curie Fellow)

    • Ideated and implemented an innovative algorithm for segmenting lip and hand movements from Cued Speech videos. Published and presented the results of this work at INTERSPEECH 2023
    • Engineered end-to-end ACSR systems, achieving a 15.2% improvement in recognition accuracy at phonetic level and presented the findings at ICASSP 2022
    • Currently exploring generative models for small data to develop the first-ever CS Generation framework
    • Released a curated clean mono-blications
    cuer dataset for CS (DOI: 10.5281/zenodo.8392608)
    • Actively involved in data collection efforts to establish the first French multi-cuer corpus

    [1] S. Sankar, D. Beautemps, F. Elisei, O. Perrotin, T. Hueber, “Investigating the dynamics of hand and lips in
    French Cued Speech using attention mechanisms and CTC-based decoding”, INTERSPEECH 2023, DOI: 10.1109/ICASSP43922.2022.9746976
    [2] S. Sankar, D. Beautemps, T. Hueber, “Multistream Neural Architectures for Cued Speech Recognition using
    Pre-trained Feature Extractor and Constrained CTC Decoding”, ICASSP 2022, DOI: 10.21437/Interspeech.2023-1669
    [3] Public access dataset released with [2] on Zenodo – DOI: 10.5281/zenodo.8392608

    • Collaborated with Ivès to test and implement an online data collection software for CS and sign language
    • Visiting researcher at the University de Libre Bruxelles – EU collab project for intersectoral exposure among researchers

  • 2020 - 2021
    Indian Institute of Technology Madras (IITM)

    Project Associate

    • Devised and deployed a highly effective end-to-end Indian-English ASR ( system for the automatic transcription of NPTEL ( courses, significantly improving transcription accuracy and streamlining the learning experience
    • Implemented the baseline for the Hindi ASR Challenge ( and monitored the submissions
    • Worked on enhancing speaker diarization systems and extracting speaker embeddings for voice conversion

  • 2019 - 2020
    Indian Institute of Information Technology Design and Manufacturing

    Research Masters Student (Thesis)

    • Revamped adaptive filtering algorithms with kernel methods to reduce non-linear echo return loss in audio devices
    • The above project culminated as a journal publication in Applied Acoustics (DOI: 10.1016/j.apacoust.2020.107329)
    • Pioneered the development of a novel collaborative scheme for non-linear stereophonic acoustic echo cancellation, a key contribution acknowledged in the Journal of AIHC (DOI: 10.1007/s12652-021-03647-2)

  • 2019 - 2019
    Technische Universitat Dresden

    Research Intern

    • Developed a compact module of a Grapheme-to-Phoneme converter and interfaced it with the VocalTractLab (
    • Ported SEQUITUR algorithm from Windows and revamped for a Linux platform


Artificial Intelligence
Machine Learning
Deep Learning
Speech Processing
Audio Processing
Image Processing
Language Model



Honors & awards


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