22 citations · 52 across the 21 of their papers we have counts for
5 papers · 1 filter
WACO: Word-Aligned Contrastive Learning for Speech Translation
Siqi Ouyang, Rong Ye, Lei Li
End-to-end Speech Translation (E2E ST) aims to directly translate source speech into target text. Existing ST methods perform poorly when only extremely small speech-text data are…
On the Impact of Noises in Crowd-Sourced Data for Speech Translation
Siqi Ouyang, Rong Ye, Lei Li
Training speech translation (ST) models requires large and high-quality datasets. MuST-C is one of the most widely used ST benchmark datasets. It contains around 400 hours of speec…
Cross-modal Contrastive Learning for Speech Translation
Rong Ye, Mingxuan Wang, Lei Li
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 sp…
GigaST: A 10,000-hour Pseudo Speech Translation Corpus
Rong Ye, Chengqi Zhao, Tom Ko +4
This paper introduces GigaST, a large-scale pseudo speech translation (ST) corpus. We create the corpus by translating the text in GigaSpeech, an English ASR corpus, into German an…
STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation
Qingkai Fang, Rong Ye, Lei Li +2
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…