The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …

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 …

What does it take to create the Babel Fish, a tool that can help individuals translate speech
between any two languages? While recent breakthroughs in text-based models have …

Large-scale automatic speech translation systems today lack key features that help machine-
mediated communication feel seamless when compared to human-to-human dialogue. In …

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

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 …

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 …

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 …

Direct speech-to-speech translation (S2ST), in which all components can be optimized
jointly, is advantageous over cascaded approaches to achieve fast inference with a …