11 citations · 20 across the 15 of their papers we have counts for
18 papers
Ouvia: A User-centered Framework for Measuring Usability of Speech Translation in Real-World Communication Scenarios
Giuseppe Attanasio, Beatrice Savoldi, Daniel Chechelnitsky +4
Speech translation (ST) is increasingly adopted in user applications, yet its evaluation largely focuses on decontextualized testbeds and holistic quality, rather than end users' c…
Gender-Neutral Rewriting in Italian: Models, Approaches, and Trade-offs
Andrea Piergentili, Beatrice Savoldi, Matteo Negri +1
Gender-neutral rewriting (GNR) aims to reformulate text to eliminate unnecessary gender specifications while preserving meaning, a particularly challenging task in grammatical-gend…
Mind the Inclusivity Gap: Multilingual Gender-Neutral Translation Evaluation with mGeNTE
Beatrice Savoldi, Giuseppe Attanasio, Eleonora Cupin +7
Avoiding the propagation of undue (binary) gender inferences and default masculine language remains a key challenge towards inclusive multilingual technologies, particularly when t…
GFG -- Gender-Fair Generation: A CALAMITA Challenge
Simona Frenda, Andrea Piergentili, Beatrice Savoldi +7
Gender-fair language aims at promoting gender equality by using terms and expressions that include all identities and avoid reinforcing gender stereotypes. Implementing gender-fair…
SPES: Spectrogram Perturbation for Explainable Speech-to-Text Generation
Dennis Fucci, Marco Gaido, Beatrice Savoldi +3
Spurred by the demand for interpretable models, research on eXplainable AI for language technologies has experienced significant growth, with feature attribution methods emerging a…
What the Harm? Quantifying the Tangible Impact of Gender Bias in Machine Translation with a Human-centered Study
Beatrice Savoldi, Sara Papi, Matteo Negri +2
Gender bias in machine translation (MT) is recognized as an issue that can harm people and society. And yet, advancements in the field rarely involve people, the final MT users, or…
Enhancing Gender-Inclusive Machine Translation with Neomorphemes and Large Language Models
Andrea Piergentili, Beatrice Savoldi, Matteo Negri +1
Machine translation (MT) models are known to suffer from gender bias, especially when translating into languages with extensive gendered morphology. Accordingly, they still fall sh…
A Prompt Response to the Demand for Automatic Gender-Neutral Translation
Beatrice Savoldi, Andrea Piergentili, Dennis Fucci +2
Gender-neutral translation (GNT) that avoids biased and undue binary assumptions is a pivotal challenge for the creation of more inclusive translation technologies. Advancements fo…
Twists, Humps, and Pebbles: Multilingual Speech Recognition Models Exhibit Gender Performance Gaps
Giuseppe Attanasio, Beatrice Savoldi, Dennis Fucci +1
Current automatic speech recognition (ASR) models are designed to be used across many languages and tasks without substantial changes. However, this broad language coverage hides p…
Test Suites Task: Evaluation of Gender Fairness in MT with MuST-SHE and INES
Beatrice Savoldi, Marco Gaido, Matteo Negri +1
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. By focusing on the en-de and de-e…
Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus
Andrea Piergentili, Beatrice Savoldi, Dennis Fucci +2
Gender inequality is embedded in our communication practices and perpetuated in translation technologies. This becomes particularly apparent when translating into grammatical gende…
Good, but not always Fair: An Evaluation of Gender Bias for three commercial Machine Translation Systems
Silvia Alma Piazzolla, Beatrice Savoldi, Luisa Bentivogli
Machine Translation (MT) continues to make significant strides in quality and is increasingly adopted on a larger scale. Consequently, analyses have been redirected to more nuanced…
Gender Neutralization for an Inclusive Machine Translation: from Theoretical Foundations to Open Challenges
Andrea Piergentili, Dennis Fucci, Beatrice Savoldi +2
Gender inclusivity in language technologies has become a prominent research topic. In this study, we explore gender-neutral translation (GNT) as a form of gender inclusivity and a…
Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translation
Beatrice Savoldi, Marco Gaido, Luisa Bentivogli +2
Gender bias is largely recognized as a problematic phenomenon affecting language technologies, with recent studies underscoring that it might surface differently across languages.…
How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation
Marco Gaido, Beatrice Savoldi, Luisa Bentivogli +2
Having recognized gender bias as a major issue affecting current translation technologies, researchers have primarily attempted to mitigate it by working on the data front. However…
Gender Bias in Machine Translation
Beatrice Savoldi, Marco Gaido, Luisa Bentivogli +2
Machine translation (MT) technology has facilitated our daily tasks by providing accessible shortcuts for gathering, elaborating and communicating information. However, it can suff…
Breeding Gender-aware Direct Speech Translation Systems
Marco Gaido, Beatrice Savoldi, Luisa Bentivogli +2
In automatic speech translation (ST), traditional cascade approaches involving separate transcription and translation steps are giving ground to increasingly competitive and more r…
Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus
Luisa Bentivogli, Beatrice Savoldi, Matteo Negri +3
Translating from languages without productive grammatical gender like English into gender-marked languages is a well-known difficulty for machines. This difficulty is also due to t…