The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …

In recent years, natural language processing (NLP) has got great development with deep
learning techniques. In the sub-field of machine translation, a new approach named Neural …

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 …

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 a recurrent encoder-decoder deep neural network architecture that directly
translates speech in one language into text in another. The model does not explicitly …

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 …

This paper proposes a first attempt to build an end-to-end speech-to-text translation system,
which does not use source language transcription during learning or decoding. We propose …

We investigate end-to-end speech-to-text translation on a corpus of audiobooks specifically
augmented for this task. Previous works investigated the extreme case where source …

End-to-end speech translation (ST), which directly translates from source language speech
into target language text, has attracted intensive attentions in recent years. Compared to …

We explore multitask models for neural translation of speech, augmenting them in order to
reflect two intuitive notions. First, we introduce a model where the second task decoder …