ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2006.05754
  4. Cited By
Gender in Danger? Evaluating Speech Translation Technology on the
  MuST-SHE Corpus

Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus

10 June 2020
L. Bentivogli
Beatrice Savoldi
Matteo Negri
Mattia Antonino Di Gangi
R. Cattoni
Marco Turchi
ArXivPDFHTML

Papers citing "Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus"

8 / 8 papers shown
Title
Are We Paying Attention to Her? Investigating Gender Disambiguation and Attention in Machine Translation
Are We Paying Attention to Her? Investigating Gender Disambiguation and Attention in Machine Translation
Chiara Manna
Afra Alishahi
Frédéric Blain
Eva Vanmassenhove
22
0
0
13 May 2025
GATE X-E : A Challenge Set for Gender-Fair Translations from
  Weakly-Gendered Languages
GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages
Spencer Rarrick
Ranjita Naik
Sundar Poudel
Vishal Chowdhary
32
1
0
22 Feb 2024
Efficient CTC Regularization via Coarse Labels for End-to-End Speech
  Translation
Efficient CTC Regularization via Coarse Labels for End-to-End Speech Translation
Biao Zhang
Barry Haddow
Rico Sennrich
15
3
0
21 Feb 2023
What Do Compressed Multilingual Machine Translation Models Forget?
What Do Compressed Multilingual Machine Translation Models Forget?
Alireza Mohammadshahi
Vassilina Nikoulina
Alexandre Berard
Caroline Brun
James Henderson
Laurent Besacier
AI4CE
40
9
0
22 May 2022
CoCoA-MT: A Dataset and Benchmark for Contrastive Controlled MT with
  Application to Formality
CoCoA-MT: A Dataset and Benchmark for Contrastive Controlled MT with Application to Formality
Maria Nadejde
Anna Currey
B. Hsu
Xing Niu
Marcello Federico
Georgiana Dinu
22
24
0
09 May 2022
A Survey on Gender Bias in Natural Language Processing
A Survey on Gender Bias in Natural Language Processing
Karolina Stañczak
Isabelle Augenstein
28
109
0
28 Dec 2021
Don't speak too fast: The impact of data bias on self-supervised speech
  models
Don't speak too fast: The impact of data bias on self-supervised speech models
Yen Meng
Yi-Hui Chou
Andy T. Liu
Hung-yi Lee
34
24
0
15 Oct 2021
Evaluating Gender Bias in Speech Translation
Evaluating Gender Bias in Speech Translation
Marta R. Costa-jussá
Christine Basta
Gerard I. Gállego
16
20
0
27 Oct 2020
1