6 citations · 10 across the 4 of their papers we have counts for
4 papers · 1 filter
Curriculum Learning for Domain Adaptation in Neural Machine Translation
Xuan Zhang, Pamela Shapiro, Gaurav Kumar +3
We introduce a curriculum learning approach to adapt generic neural machine translation models to a specific domain. Samples are grouped by their similarities to the domain of inte…
An Empirical Exploration of Curriculum Learning for Neural Machine Translation
Xuan Zhang, Gaurav Kumar, Huda Khayrallah +6
Machine translation systems based on deep neural networks are expensive to train. Curriculum learning aims to address this issue by choosing the order in which samples are presente…
Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation
Brian Thompson, Huda Khayrallah, Antonios Anastasopoulos +7
To better understand the effectiveness of continued training, we analyze the major components of a neural machine translation system (the encoder, decoder, and each embedding space…
Using of heterogeneous corpora for training of an ASR system
Jan Trmal, Gaurav Kumar, Vimal Manohar +3
The paper summarizes the development of the LVCSR system built as a part of the Pashto speech-translation system at the SCALE (Summer Camp for Applied Language Exploration) 2015 wo…