MULTILINGUAL UNSUPERVISED NEURAL MACHINE TRANSLATION WITH DENOISING ADAPTERS
摘要:
Methods and systems for unsupervised training for a neural multilingual sequence-to-sequence (seq2seq) model. Denoising adapters for each of one or more languages is inserted into an encoder and/or a decoder of the seq2seq model. Parameters of the one or more denoising adapters are trained on a language-specific denoising task using monolingual text for each of the one or more languages. Cross-attention weights of the seq2seq model with the trained denoising adapter layers are fine-tuned on a translation task in at least one of the one or more languages with parallel data.
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