José A.R. Fonollosa

SegAugment: Maximizing the Utility of Speech Translation Data with Segmentation-based Augmentations

End-to-end Speech Translation is hindered by a lack of available data resources. While most of them are based on documents, a sentence-level version is available, which is however single and static, potentially impeding the usefulness of the data. We propose a new data augmentation strategy, SegAugm…