August 8, 2018 alignments, NLP Leave a comment

Issue #4 – Six Challenges in Neural MT

08 Aug18 Issue #4 – Six Challenges in Neural MT Author: Dr. John Tinsley, CEO @ Iconic A little over a year ago, Koehn and Knowles (2017) wrote a very appropriate paper entitled “Six Challenges in Neural Machine Translation” (in fact, there were 7 but only 6 were empirically tested). The paper set out a number of areas which, despite its rapid development, still needed to be addressed by researchers and developers of Neural MT. The seven challenges posed at […]

July 25, 2018 Data Cleaning, NLP Leave a comment

Issue #2 – Data Cleaning for Neural MT

25 Jul18 Issue #2 – Data Cleaning for Neural MT Author: Dr. Patrik Lambert, Machine Translation Scientist @ Iconic “Garbage in, Garbage out” – noisy data is a big problem for all machine learning tasks, and MT is no different. By noisy data, we mean bad alignments, poor translations, misspellings, and other inconsistencies in the data used to train the systems. Statistical MT systems are more robust, and can cope with up to 10% noise in the training data without […]

July 18, 2018 Distributed Synchronous SGD, NLP Leave a comment

Issue #1 – Scaling Neural MT

18 Jul18 Issue #1 – Scaling Neural MT Author: Dr. Rohit Gupta, Sr. Machine Translation Scientist @ Iconic Training a neural machine translation engine is a time consuming task. It typically takes a number of days or even weeks, when running powerful GPUs. Reducing this time is a priority of any neural MT developer. In this post we explore a recent work (Ott et al, 2018), whereby, without compromising the translation quality, they speed up the training 4.9 times on […]

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