33 citations · 121 across the 12 of their papers we have counts for
5 papers · 2 filters
On Knowledge Distillation for Direct Speech Translation
Marco Gaido, Mattia A. Di Gangi, Matteo Negri +1
Direct speech translation (ST) has shown to be a complex task requiring knowledge transfer from its sub-tasks: automatic speech recognition (ASR) and machine translation (MT). For…
On Target Segmentation for Direct Speech Translation
Mattia Antonino Di Gangi, Marco Gaido, Matteo Negri +1
Recent studies on direct speech translation show continuous improvements by means of data augmentation techniques and bigger deep learning models. While these methods are helping t…
Contextualized Translation of Automatically Segmented Speech
Marco Gaido, Mattia Antonino Di Gangi, Matteo Negri +2
Direct speech-to-text translation (ST) models are usually trained on corpora segmented at sentence level, but at inference time they are commonly fed with audio split by a voice ac…
Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus
Luisa Bentivogli, Beatrice Savoldi, Matteo Negri +3
Translating from languages without productive grammatical gender like English into gender-marked languages is a well-known difficulty for machines. This difficulty is also due to t…
End-to-End Speech-Translation with Knowledge Distillation: FBK@IWSLT2020
Marco Gaido, Mattia Antonino Di Gangi, Matteo Negri +1
This paper describes FBK's participation in the IWSLT 2020 offline speech translation (ST) task. The task evaluates systems' ability to translate English TED talks audio into Germa…