373 citations · 841 across the 71 of their papers we have counts for
12 papers · 1 filter
Detecting and Mitigating Hallucinations in Machine Translation: Model Internal Workings Alone Do Well, Sentence Similarity Even Better
David Dale, Elena Voita, Loïc Barrault +1
While the problem of hallucinations in neural machine translation has long been recognized, so far the progress on its alleviation is very little. Indeed, recently it turned out th…
BLASER: A Text-Free Speech-to-Speech Translation Evaluation Metric
Mingda Chen, Paul-Ambroise Duquenne, Pierre Andrews +4
End-to-End speech-to-speech translation (S2ST) is generally evaluated with text-based metrics. This means that generated speech has to be automatically transcribed, making the eval…
SegAugment: Maximizing the Utility of Speech Translation Data with Segmentation-based Augmentations
Ioannis Tsiamas, José A. R. Fonollosa, Marta R. Costa-jussà
End-to-end Speech Translation is hindered by a lack of available data resources. While most of them are based on documents, a sentence-level version is available, which is however…
Efficient Speech Translation with Dynamic Latent Perceivers
Ioannis Tsiamas, Gerard I. Gállego, José A. R. Fonollosa +1
Transformers have been the dominant architecture for Speech Translation in recent years, achieving significant improvements in translation quality. Since speech signals are longer…
Toxicity in Multilingual Machine Translation at Scale
Marta R. Costa-jussà, Eric Smith, Christophe Ropers +4
Machine Translation systems can produce different types of errors, some of which are characterized as critical or catastrophic due to the specific negative impact that they can hav…
No Language Left Behind: Scaling Human-Centered Machine Translation
NLLB Team, Marta R. Costa-jussà, James Cross +36
Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today. However,…
Multiformer: A Head-Configurable Transformer-Based Model for Direct Speech Translation
Gerard Sant, Gerard I. Gállego, Belen Alastruey +1
Transformer-based models have been achieving state-of-the-art results in several fields of Natural Language Processing. However, its direct application to speech tasks is not trivi…
Towards Opening the Black Box of Neural Machine Translation: Source and Target Interpretations of the Transformer
Javier Ferrando, Gerard I. Gállego, Belen Alastruey +2
In Neural Machine Translation (NMT), each token prediction is conditioned on the source sentence and the target prefix (what has been previously translated at a decoding step). How…
On the Locality of Attention in Direct Speech Translation
Belen Alastruey, Javier Ferrando, Gerard I. Gállego +1
Transformers have achieved state-of-the-art results across multiple NLP tasks. However, the self-attention mechanism complexity scales quadratically with the sequence length, creat…
Measuring the Mixing of Contextual Information in the Transformer
Javier Ferrando, Gerard I. Gállego, Marta R. Costa-jussà
The Transformer architecture aggregates input information through the self-attention mechanism, but there is no clear understanding of how this information is mixed across the enti…
A multi-task semi-supervised framework for Text2Graph & Graph2Text
Oriol Domingo, Marta R. Costa-jussà, Carlos Escolano
The Artificial Intelligence industry regularly develops applications that mostly rely on Knowledge Bases, a data repository about specific, or general, domains, usually represented…
SHAS: Approaching optimal Segmentation for End-to-End Speech Translation
Ioannis Tsiamas, Gerard I. Gállego, José A. R. Fonollosa +1
Speech translation models are unable to directly process long audios, like TED talks, which have to be split into shorter segments. Speech translation datasets provide manual segme…