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 solve the data scarcity problem for end-to-end speech-to-text translation (ST)? It's
well known that data augmentation is an efficient method to improve performance for many …

We describe the design and findings of the SIGMORPHON 2020 shared task on multilingual
grapheme-to-phoneme conversion. Participants were asked to submit systems which take in …

End-to-end speech translation relies on data that pair source-language speech inputs with
corresponding translations into a target language. Such data are notoriously scarce, making …

In this paper, we improve speech translation (ST) through effectively leveraging large
quantities of unlabeled speech and text data in different and complementary ways. We …

Direct Speech-to-speech translation (S2ST) has drawn more and more attention recently.
The task is very challenging due to data scarcity and complex speech-to-speech mapping. In …

Directly translating from speech to text using an end-to-end approach is still challenging for
many language pairs due to insufficient data. Although pretraining the encoder parameters …

We present Translatotron 2, a neural direct speech-to-speech translation model that can be
trained end-to-end. Translatotron 2 consists of a speech encoder, a phoneme decoder, a …

How to find proper moments to generate partial sentence translation given a streaming
speech input? Existing approaches waiting-and-translating for a fixed duration often break …

End-to-end speech-to-text translation can provide a simpler and smaller system but is facing
the challenge of data scarcity. Pre-training methods can leverage unlabeled data and have …