Polyglot Neural Language Models: A Case Study in Cross-Lingual Phonetic Representation Learning

NAACL 2016 Yulia TsvetkovSunayana SitaramManaal FaruquiGuillaume LamplePatrick LittellDavid MortensenAlan W BlackLori LevinChris Dyer

We introduce polyglot language models, recurrent neural network models trained to predict symbol sequences in many different languages using shared representations of symbols and conditioning on typological information about the language to be predicted. We apply these to the problem of modeling phone sequences---a domain in which universal symbol inventories and cross-linguistically shared feature representations are a natural fit... (read more)

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