On Using SpecAugment for End-to-End Speech Translation [article]

Parnia Bahar, Albert Zeyer, Ralf Schlüter, Hermann Ney
2019 arXiv   pre-print
This work investigates a simple data augmentation technique, SpecAugment, for end-to-end speech translation. SpecAugment is a low-cost implementation method applied directly to the audio input features and it consists of masking blocks of frequency channels, and/or time steps. We apply SpecAugment on end-to-end speech translation tasks and achieve up to +2.2\% \BLEU on LibriSpeech Audiobooks En->Fr and +1.2% on IWSLT TED-talks En->De by alleviating overfitting to some extent. We also examine
more » ... effectiveness of the method in a variety of data scenarios and show that the method also leads to significant improvements in various data conditions irrespective of the amount of training data.
arXiv:1911.08876v1 fatcat:omlozz7m3zaifhjkrpd3kznxaa