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 …

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 …

We present ESPnet-ST, which is designed for the quick development of speech-to-speech
translation systems in a single framework. ESPnet-ST is a new project inside end-to-end …

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 …

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 progress …

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 …

Over its three decade history, speech translation has experienced several shifts in its
primary research themes; moving from loosely coupled cascades of speech recognition and …

End-to-end speech translation poses a heavy burden on the encoder, because it has to
transcribe, understand, and learn cross-lingual semantics simultaneously. To obtain a …

Multimodal machine translation involves drawing information from more than one modality,
based on the assumption that the additional modalities will contain useful alternative views …

Joint speech-language training is challenging due to the large demand for training data and
GPU consumption, as well as the modality gap between speech and language. We present …