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1
Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translation ...
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2
Gender Bias in Machine Translation ...
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3
How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation ...
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4
How to Split: the Effect of Word Segmentation on Gender Bias in Speech Translation ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.313 Abstract: 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, whether algorithmic aspects concur to exacerbate unwanted outputs remains so far under-investigated. In this work, we bring the analysis on gender bias in automatic translation onto a seemingly neutral yet critical component: word segmentation. Can segmenting methods influence the ability to translate gender? Do certain segmentation approaches penalize the representation of feminine linguistic markings? We address these questions by comparing 5 existing segmentation strategies on the target side of speech translation systems. Our results on two language pairs (English-Italian/French) show that state-of-the-art subword splitting (BPE) comes at the cost of higher gender bias. In light of this finding, we propose a combined approach that preserves BPE overall ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Gender Studies; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://underline.io/lecture/26404-how-to-split-the-effect-of-word-segmentation-on-gender-bias-in-speech-translation
https://dx.doi.org/10.48448/ydta-r725
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5
Is “moby dick” a Whale or a Bird? Named Entities and Terminology in Speech Translation ...
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6
Gender Bias in Machine Translation ...
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7
Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference? ...
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8
Breeding Gender-aware Direct Speech Translation Systems ...
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9
Machine translation for institutional academic texts: Output quality, terminology translation and post-editor trust
Scansani, Randy <1991>. - : Alma Mater Studiorum - Università di Bologna, 2020
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10
MuST-C A Multilingual Speech Translation Corpus (Conference slides) ...
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11
The first Automatic Translation Memory Cleaning Shared Task [<Journal>]
Barbu, Eduard [Verfasser]; Parra Escartín, Carla [Sonstige]; Bentivogli, Luisa [Sonstige].
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12
The first Automatic Translation Memory Cleaning Shared Task
In: 30 ; 3-4 ; 145 ; 166 (2017)
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13
Neural versus Phrase-Based Machine Translation Quality: a Case Study ...
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14
Creating a ground truth multilingual dataset of news and talk show transcriptions through crowdsourcing
Sprugnoli, Rachele (orcid:0000-0001-6861-5595); Moretti, Giovanni; Bentivogli, Luisa. - 2016
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15
The SICK (Sentences Involving Compositional Knowledge) dataset for relatedness and entailment ...
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16
The SICK (Sentences Involving Compositional Knowledge) dataset for relatedness and entailment ...
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17
SemEval-2013 Task 7: The Joint Student Response Analysis and 8th Recognizing Textual Entailment Challenge
In: DTIC (2013)
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18
SemEval-2013 Task 7: The Joint Student Response Analysis and 8th Recognizing Textual Embodiment Challenge
In: Seventh International Workshop on Semantic Evaluation, June 14-15, 2013. Atlanta, Georgia. (2013)
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19
Exploiting parallel texts in the creation of multilingual semantically annotated resources : the MultiSemCor corpus
In: Natural language engineering. - Cambridge : Cambridge University Press 11 (2005) 3, 247-261
BLLDB
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20
SICK through the SemEval glasses: lesson learned from the evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment
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