123 citations · 402 across the 40 of their papers we have counts for
50 papers
IndicQE-APE: A Consolidated Benchmark for Quality Estimation and Automatic Post-Editing for Indic Languages
Diptesh Kanojia, Archchana Sindhujan, Sourabh Deoghare +14
Indic quality estimation (QE) and automatic post-editing (APE) data is spread across separate releases, so no single resource supports training and evaluation across tasks and lang…
FuxiTranyu: A Multilingual Large Language Model Trained with Balanced Data
Haoran Sun, Renren Jin, Shaoyang Xu +10
Large language models (LLMs) have demonstrated prowess in a wide range of tasks. However, many LLMs exhibit significant performance discrepancies between high- and low-resource lan…
Evaluating the IWSLT2023 Speech Translation Tasks: Human Annotations, Automatic Metrics, and Segmentation
Matthias Sperber, Ondřej Bojar, Barry Haddow +8
Human evaluation is a critical component in machine translation system development and has received much attention in text translation research. However, little prior work exists o…
AlignAtt: Using Attention-based Audio-Translation Alignments as a Guide for Simultaneous Speech Translation
Sara Papi, Marco Turchi, Matteo Negri
Attention is the core mechanism of today's most used architectures for natural language processing and has been analyzed from many perspectives, including its effectiveness for mac…
Attention as a Guide for Simultaneous Speech Translation
Sara Papi, Matteo Negri, Marco Turchi
The study of the attention mechanism has sparked interest in many fields, such as language modeling and machine translation. Although its patterns have been exploited to perform di…
Joint Speech Translation and Named Entity Recognition
Marco Gaido, Sara Papi, Matteo Negri +1
Modern automatic translation systems aim at place the human at the center by providing contextual support and knowledge. In this context, a critical task is enriching the output wi…
Direct Speech Translation for Automatic Subtitling
Sara Papi, Marco Gaido, Alina Karakanta +3
Automatic subtitling is the task of automatically translating the speech of audiovisual content into short pieces of timed text, i.e. subtitles and their corresponding timestamps.…
Dodging the Data Bottleneck: Automatic Subtitling with Automatically Segmented ST Corpora
Sara Papi, Alina Karakanta, Matteo Negri +1
Speech translation for subtitling (SubST) is the task of automatically translating speech data into well-formed subtitles by inserting subtitle breaks compliant to specific display…
Over-Generation Cannot Be Rewarded: Length-Adaptive Average Lagging for Simultaneous Speech Translation
Sara Papi, Marco Gaido, Matteo Negri +1
Simultaneous speech translation (SimulST) systems aim at generating their output with the lowest possible latency, which is normally computed in terms of Average Lagging (AL). In t…
Who Are We Talking About? Handling Person Names in Speech Translation
Marco Gaido, Matteo Negri, Marco Turchi
Recent work has shown that systems for speech translation (ST) -- similarly to automatic speech recognition (ASR) -- poorly handle person names. This shortcoming does not only lead…
Efficient yet Competitive Speech Translation: FBK@IWSLT2022
Marco Gaido, Sara Papi, Dennis Fucci +3
The primary goal of this FBK's systems submission to the IWSLT 2022 offline and simultaneous speech translation tasks is to reduce model training costs without sacrificing translat…
Does Simultaneous Speech Translation need Simultaneous Models?
Sara Papi, Marco Gaido, Matteo Negri +1
In simultaneous speech translation (SimulST), finding the best trade-off between high translation quality and low latency is a challenging task. To meet the latency constraints pos…
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.…
Visualization: the missing factor in Simultaneous Speech Translation
Sara Papi, Matteo Negri, Marco Turchi
Simultaneous speech translation (SimulST) is the task in which output generation has to be performed on partial, incremental speech input. In recent years, SimulST has become popul…
Is "moby dick" a Whale or a Bird? Named Entities and Terminology in Speech Translation
Marco Gaido, Susana Rodríguez, Matteo Negri +2
Automatic translation systems are known to struggle with rare words. Among these, named entities (NEs) and domain-specific terms are crucial, since errors in their translation can…
Speechformer: Reducing Information Loss in Direct Speech Translation
Sara Papi, Marco Gaido, Matteo Negri +1
Transformer-based models have gained increasing popularity achieving state-of-the-art performance in many research fields including speech translation. However, Transformer's quadr…
Simultaneous Speech Translation for Live Subtitling: from Delay to Display
Alina Karakanta, Sara Papi, Matteo Negri +1
With the increased audiovisualisation of communication, the need for live subtitles in multilingual events is more relevant than ever. In an attempt to automatise the process, we a…
Between Flexibility and Consistency: Joint Generation of Captions and Subtitles
Alina Karakanta, Marco Gaido, Matteo Negri +1
Speech translation (ST) has lately received growing interest for the generation of subtitles without the need for an intermediate source language transcription and timing (i.e. cap…
Dealing with training and test segmentation mismatch: FBK@IWSLT2021
Sara Papi, Marco Gaido, Matteo Negri +1
This paper describes FBK's system submission to the IWSLT 2021 Offline Speech Translation task. We participated with a direct model, which is a Transformer-based architecture train…
Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference?
Luisa Bentivogli, Mauro Cettolo, Marco Gaido +4
Five years after the first published proofs of concept, direct approaches to speech translation (ST) are now competing with traditional cascade solutions. In light of this steady p…
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…
Beyond Voice Activity Detection: Hybrid Audio Segmentation for Direct Speech Translation
Marco Gaido, Matteo Negri, Mauro Cettolo +1
The audio segmentation mismatch between training data and those seen at run-time is a major problem in direct speech translation. Indeed, while systems are usually trained on manua…
Self-Learning for Zero Shot Neural Machine Translation
Surafel M. Lakew, Matteo Negri, Marco Turchi
Neural Machine Translation (NMT) approaches employing monolingual data are showing steady improvements in resource rich conditions. However, evaluations using real-world low-resour…