Working with Visionaries on the Frontlines of Scientific Progress Worldwide
Nuance Foundation Grants

Human Language Technology and Pattern Recognition Group

 

The research activities of the Human Language Technology and Pattern Recognition Group cover the following applications:

Project: Decipherment-Based Machine Translation

Hermann Ney

Conventional statistical machine translation (MT) systems require a large set of (source, target) sentence pairs for training. Such a bilingual corpus is not available for all language pairs (and not for all domains). On the other hand, a huge amount of monolingual data is available for many languages so that a high-quality language model can be learned. From this point of view, the training problem for statistical machine translation can be reformulated as a decipherment problem: we are given a (maybe very) large set of sentences in the source language, and we want to find the associated translations in the target language, whose language model is given. Due to the implicit word-to-word correspondences between the two languages, this formulation amounts to a combinatorial problem, in which both the (source word, target word)-pairs and their probabilities are unknown.

Publications: TBD

Programs & Grants

100 years ago nobody would have imagined that it may make sense to talk to machines. Today, in the days of speech recognition and speech synthesis to be found in cars, computers, phones and many other devices this is already normal. But it doesn't stop there.

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