Andrea Piergentili

PhD student

    Short bio

    Andrea Piergentili is a PhD student at the University of Trento and Fondazione Bruno Kessler, where he works in the Machine Translation unit.

    He obtained his BD and MD in modern languages at the University of L'Aquila.
    His research focuses on gender-inclusive language in machine translation (MT).
    This involves avoiding discriminatory practices, such as misgendering, stereotypical associations, and exclusionary language, as a way to make MT fair and inclusive of all gender identities.


    1. Piergentili, Andrea; Fucci, Dennis; Savoldi, Beatrice; Bentivogli, Luisa; Negri, Matteo,
      Proceedings of the First Workshop on Gender-Inclusive Translation Technologies (GITT 2023),
      European Association for Machine Translation,
      , pp. 71-
    2. Piergentili, Andrea; Savoldi, Beatrice; Fucci, Dennis; Negri, Matteo; Bentivogli, Luisa,
      Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing,
      Association for Computational Linguistics,
      , pp. 14124-

    I am super happy to share that I co-authored 4 papers accepted at the #ACL2024NLP main conference!

    2 preprints already available about:
    -software quality in NLP:
    - speech translation:

    Other preprints and more details coming soon!

    The day started with fantastic news: our 4 long papers have been accepted at the #ACL2024NLP main conference! And we have just released #opensource two new repos:
    - for unit testing your architectures
    - to evaluate SRT quality

    Bandi a cascata FAIR: aperta la call dello Spoke 2 (@FBK_research @Unitrento) per progetti su #intelligenzaartificiale da #PMI, #aziende e #startup.

    📅Scadenza 6 giugno 2024
    ➡️Bando su:

    #PNRR #IA #AI #bandi #innovazione

    Our pick of the week by @DennisFucci: "Encoding of lexical tone in self-supervised models of spoken language" by @linguisticshen, @Phonologician
    @afraalishahi, @AriannaBisazza, and @gchrupala, NAACL 2024.

    #Speech #SpokenLanguageModels #ToneEncoding #Interpretability #Phonology

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