37 citations · 277 across the 41 of their papers we have counts for
13 papers · 1 filter
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…
CTC-based Compression for Direct Speech Translation
Marco Gaido, Mauro Cettolo, Matteo Negri +1
Previous studies demonstrated that a dynamic phone-informed compression of the input audio is beneficial for speech translation (ST). However, they required a dedicated model for p…
The Multilingual TEDx Corpus for Speech Recognition and Translation
Elizabeth Salesky, Matthew Wiesner, Jacob Bremerman +5
We present the Multilingual TEDx corpus, built to support speech recognition (ASR) and speech translation (ST) research across many non-English source languages. The corpus is a co…