How to learn a better speech representation for end-to-end speech-to-text translation (ST)
with limited labeled data? Existing techniques often attempt to transfer powerful machine …

Recently, speech-to-text translation has attracted more and more attention and many studies
have emerged rapidly. In this paper, we present a comprehensive survey on direct speech …

The evaluation campaign of the 19th International Conference on Spoken Language
Translation featured eight shared tasks:(i) Simultaneous speech translation,(ii) Offline …

How can we learn unified representations for spoken utterances and their written text?
Learning similar representations for semantically similar speech and text is important for …

Adapter modules were recently introduced as an efficient alternative to fine-tuning in NLP.
Adapter tuning consists in freezing pretrained parameters of a model and injecting …

Abstract Speech-to-Text (ST) translation pertains to the task of converting speech signals in
one language to text in another language. It finds its application in various domains, such as …

Having numerous potential applications and great impact, end-to-end speech translation
(ST) has long been treated as an independent task, failing to fully draw strength from the …

End-to-end speech translation models have become a new trend in research due to their
potential of reducing error propagation. However, these models still suffer from the …

Recently, representation learning for text and speech has successfully improved many
language related tasks. However, all existing methods suffer from two limitations:(a) they …

End-to-end speech translation (ST) is the task of translating speech signals in the source
language into text in the target language. As a cross-modal task, end-to-end ST is difficult to …