Beomseok Lee

PhD Student

    Short bio

    Beomseok Lee is a PhD student at the University of Trento, conducting research at Fondazione Bruno Kessler and NAVER LABS Europe.

    Before starting his PhD, Beomseok worked as a full-time research engineer at SAMSUNG Research (Samsung Electronics R&D hub) Global AI Center, Seoul where he specialized in End-to-end (E2E) Speech-to-text translation. His current research focuses on E2E Spoken Language Understanding with an emphasis on multi-task, multi-lingual and multi-modal approaches. He holds a Computer Science (CS) Master's degree from Korea Advanced Institute of Science & Technology (KAIST, Korea) and a CS Bachelor's degree from Sungkyunkwan University (SKKU, Korea).

    Research topics

    Spoken Language Understanding, Multi-modality

    Publications

    1. Lee, Beomseok; Gaido, Marco; Calapodescu, Ioan; Besacier, Laurent; Negri, Matteo,
      in «»,
      Proceedings of the 31st International Conference on Computational Linguistics,
      ,
      vol. ,
      n. ,
      2025
      , pp. 6816-
      6826
    2. Lee, Beomseok; Calapodescu, Ioan; Gaido, Marco; Negri, Matteo; Besacier, Laurent,
      in «»,
      Proceedings of Interspeech2024,
      ,
      vol. ,
      n. ,
      2024
      , pp. 817-
      821

    ⭐ For our #PickOfTheWeek, this paper explores an important question for modern speech AI:

    🎙️ Which Evaluation for Which Speech Model?
    👥 Authors: @Maureendss , @EeshanDhekane

    Speech foundation models are evolving rapidly, but evaluation practices are still fragmented.

    🏝️ Yesterday at #LREC2026, Palma de Mallorca!
    @lina_conti presented "Voice, Bias, and Coreference: An Interpretability Study of Gender in Speech Translation" at the poster session.
    📄Paper:
    💻Code: https://github.com/lina-conti/voice-bias-coreference
    #SpeechTranslation #NLProc

    How does the granularity of speech-text pairs impact SpeechLLM performance, and what is the optimal way to interleave tokens? Furthermore, what are the best practices for generating synthetic data to boost training?🧐

    Load More