Search Results for author: Beatrice Savoldi

Found 12 papers, 6 papers with code

On the Dynamics of Gender Learning in Speech Translation

no code implementations NAACL (GeBNLP) 2022 Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, Marco Turchi

In this work, we contribute to such a line of inquiry by exploring the emergence of gender bias in Speech Translation (ST).

Translation

A Prompt Response to the Demand for Automatic Gender-Neutral Translation

no code implementations8 Feb 2024 Beatrice Savoldi, Andrea Piergentili, Dennis Fucci, Matteo Negri, Luisa Bentivogli

Gender-neutral translation (GNT) that avoids biased and undue binary assumptions is a pivotal challenge for the creation of more inclusive translation technologies.

Machine Translation Translation

Test Suites Task: Evaluation of Gender Fairness in MT with MuST-SHE and INES

1 code implementation30 Oct 2023 Beatrice Savoldi, Marco Gaido, Matteo Negri, Luisa Bentivogli

As part of the WMT-2023 "Test suites" shared task, in this paper we summarize the results of two test suites evaluations: MuST-SHE-WMT23 and INES.

Fairness

Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translation

1 code implementation ACL 2022 Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, Marco Turchi

Gender bias is largely recognized as a problematic phenomenon affecting language technologies, with recent studies underscoring that it might surface differently across languages.

POS Translation

How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation

1 code implementation Findings (ACL) 2021 Marco Gaido, Beatrice Savoldi, Luisa Bentivogli, Matteo Negri, Marco Turchi

In light of this finding, we propose a combined approach that preserves BPE overall translation quality, while leveraging the higher ability of character-based segmentation to properly translate gender.

Segmentation Translation

Gender Bias in Machine Translation

1 code implementation13 Apr 2021 Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, Marco Turchi

Machine translation (MT) technology has facilitated our daily tasks by providing accessible shortcuts for gathering, elaborating and communicating information.

Machine Translation Translation

Breeding Gender-aware Direct Speech Translation Systems

no code implementations COLING 2020 Marco Gaido, Beatrice Savoldi, Luisa Bentivogli, Matteo Negri, Marco Turchi

In particular, by translating speech audio data without intermediate transcription, direct ST models are able to leverage and preserve essential information present in the input (e. g. speaker's vocal characteristics) that is otherwise lost in the cascade framework.

Machine Translation Translation

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