Amazon Technologies, Inc.

Prashant Mathur

Georgiana Dinu

Aakash Upadhyay

Eric J Nowell

Rama Krishna Sandeep Pokkunuri

Xianglong Huang

Yaser Al-Onaizan

Jian Wang

Marcello Federico

Anna Currey

Dengke Liu

Cuong Hoang

Haiyu Yao

Devendra Singh Sachan

Systems and methods are provided for use of use of fuzzy-match-based translation suggestions to augment machine translation of input sentences or other texts. A machine translation system may use a model trained to translate a source language input to a target language output based on pseudo-randomly selected translation suggestions in the target language, while at inference time the machine translation system may use translation selections associated with source language samples that have a high degree of similarity to the source language input to be translated. To efficiently use the translation suggestions, they may be encoded in context with the source language input to be translated, and the machine translation system may use the encoded translation suggestions with to generate a translation in the target language.

Fuzzy-match augmented machine translation

Machine learning translation models may be selectively tuned to provide custom machine translations. A request to translate input text from an input language to a target language may be received. A tuning data set for translating the input text to the target language may be identified and searched to select pairs of texts in the tuning data according to comparisons with the input text. A machine learning model used to translate into the target language may be tuned using only second texts in the target language in the selected pairs of texts. The tuned machine learning model may then be used to translate the input text into the target language.

Selectively tuning machine translation models for custom machine translations

A translation system receives examples of translations between a first language and a second language. In response to receiving request to translate a source text from the first language to the second language, the system ranks the examples based on the example's applicability to one or more portions of the source text. The system performs additional training of a neural network that was pre-trained to translate from the first language to the second language, where the additional training is based on one or more top-ranking examples. The system translates the source text to the second language using the additionally trained neural network.

Machine translation with adapted neural networks

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Prashant Mathur