Method for training machine translation model for generating pseudo parallel translation data, method for obtaining pseudo parallel translation data, and method for training machine translation model

A training method for a machine translation model for generating pseudo parallel translation data comprising:

• an initialization step of performing training processing for the machine translation model for generating pseudo parallel translation data using
• an other-domains parallel translation data set Dsetp(L1-L2) containing a plurality of pieces of parallel translation data comprising other-domains first language data, which is data for a domain other than an adaptation target domain that is a domain for which pseudo parallel translation data is to be generated, and other-domains second language data, which is translated data in a second language of the other-domains first language data,
• an other-domains monolingual data set Dsetm(L1) containing a plurality of pieces of first language data for a domain other than the adaptation target domain,
• an other-domains monolingual data set Dsetm(L2) containing a plurality of pieces of second language data for a domain other than the adaptation target domain,
• an adaptation target domain monolingual data set Dsetm(R1) containing a plurality of pieces of data of the first language of the adaptation target domain, and
• an adaptation target domain monolingual data set Dsetm(R2) containing a plurality of pieces of data of the second language of the adaptation target domain, and
• setting parameters that have been set for the machine translation model for generating pseudo parallel translation data after performing the training processing to initial parameters;
• and
• an optimization step of obtaining optimum parameters for the machine translation model for generating pseudo parallel translation data by performing training processing using at least one of
• (1) auto-encoding processing that sets correct data to the same data as input data and then performs training processing for the machine translation model for generating pseudo parallel translation data with the initial parameters set,
• (2) zero-shot round-trip machine translation processing that inputs again output data from the machine translation model for generating pseudo parallel translation data for the input data into the machine translation model for generating pseudo parallel translation data, and then performs training processing for the machine translation model for generating pseudo parallel translation data so that the output from the machine translation model for generating pseudo parallel translation data becomes the same data as the input data, for the machine translation model for generating pseudo parallel translation data with the initial parameters set, and
• (3) supervised machine translation processing that sets one of first language data and second language data included in an other-domains translation data set Dsetp(L1-L2) to an input into the machine translation model for generating pseudo parallel translation data and sets the other to correct data, and then performs training processing for the machine translation model for generating pseudo parallel translation data with the initial parameters set.