22 citations · 79 across the 14 of their papers we have counts for
3 papers · 1 filter
Analyzing the Use of Influence Functions for Instance-Specific Data Filtering in Neural Machine Translation
Tsz Kin Lam, Eva Hasler, Felix Hieber
Customer feedback can be an important signal for improving commercial machine translation systems. One solution for fixing specific translation errors is to remove the related erro…
Make More of Your Data: Minimal Effort Data Augmentation for Automatic Speech Recognition and Translation
Tsz Kin Lam, Shigehiko Schamoni, Stefan Riezler
Data augmentation is a technique to generate new training data based on existing data. We evaluate the simple and cost-effective method of concatenating the original data examples…
Sample, Translate, Recombine: Leveraging Audio Alignments for Data Augmentation in End-to-end Speech Translation
Tsz Kin Lam, Shigehiko Schamoni, Stefan Riezler
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, makin…