Recently, the speech community is seeing a significant trend of moving from deep neural
network based hybrid modeling to end-to-end (E2E) modeling for automatic speech …

Big data analytics has become a significant trend for many businesses as a result of the
daily acquisition of enormous volumes of data. This information has been gathered because …

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 …

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 …

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 …

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 …

Pretraining and multitask learning are widely used to improve the speech to text translation
performance. In this study, we are interested in training a speech to text translation model …

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 …

Abstract End-to-end (E2E) speech-to-text translation (ST) often depends on pretraining its
encoder and/or decoder using source transcripts via speech recognition or text translation …

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 …