After more than 70 years of evolution, great achievements have been made in machine
translation. Especially in recent years, translation quality has been greatly improved with the …

Abstract Machine translation is an important and challenging task that aims at automatically
translating natural language sentences from one language into another. Recently …

We introduce fairseq S2T, a fairseq extension for speech-to-text (S2T) modeling tasks such
as end-to-end speech recognition and speech-to-text translation. It follows fairseq's careful …

Current research on spoken language translation (SLT) has to confront with the scarcity of
sizeable and publicly available training corpora. This problem hinders the adoption of neural …

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 …

End-to-end spoken language translation (SLT) has recently gained popularity thanks to the
advancement of sequence to sequence learning in its two parent tasks: automatic speech …

We present a simple yet effective approach to build multilingual speech-to-text (ST)
translation by efficient transfer learning from pretrained speech encoder and text decoder …

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 …

Speech translation (ST) is an increasingly popular topic of research, partly due to the
development of benchmark datasets. Nevertheless, current datasets cover a limited number …

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 …