A method and apparatus are provided that analyzing sequence-to-sequence data, such as sequence-to-sequence speech data or sequence-to-sequence machine translation data for example, by minimum Bayes risk (MBR) training a sequence-to-sequence model and within introduction of applications of softmax smoothing to an N-best generation of the MBR training of the sequence-to-sequence model.

A method and apparatus are provided that analyzing sequence-to-sequence data, such as sequence-to-sequence speech data or sequence-to-sequence machine translation data for example, by minimum Bayes risk (MBR) training a sequence-to-sequence model and within introduction of applications of softmax smoothing to an N-best generation of the MBR training of the sequence-to-sequence model.

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.

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.

A method of translating instructions for operating electromechanical systems includes identifying an operating-language instruction from one or more operating-language instructions at least based on user information that includes a type of an electromechanical system and a desired operation. The method further includes determining whether one or more existing translated parameters are available to the computing device. The method also includes, in response to the one or more existing translated parameters being available to the computing device, identifying an existing translated parameter from among the one or more existing translated parameters at least based on a level of relevancy of the existing translated parameter to one or more user parameters, where the existing translated parameter has a highest level of relevancy to the one or more user parameters. The method also includes generating, by the computing device, a translated instruction from the operating-language instruction.

A method of translating instructions for operating electromechanical systems includes identifying an operating-language instruction from one or more operating-language instructions at least based on user information that includes a type of an electromechanical system and a desired operation. The method further includes determining whether one or more existing translated parameters are available to the computing device. The method also includes, in response to the one or more existing translated parameters being available to the computing device, identifying an existing translated parameter from among the one or more existing translated parameters at least based on a level of relevancy of the existing translated parameter to one or more user parameters, where the existing translated parameter has a highest level of relevancy to the one or more user parameters. The method also includes generating, by the computing device, a translated instruction from the operating-language instruction.

Provided are an apparatus and method for providing a personal assistant service based on automatic translation. The apparatus for providing a personal assistant service based on automatic translation includes an input section configured to receive a command of a user, a memory in which a program for providing a personal assistant service according to the command of the user is stored, and a processor configured to execute the program. The processor updates at least one of a speech recognition model, an automatic interpretation model, and an automatic translation model on the basis of an intention of the command of the user using a recognition result of the command of the user and provides the personal assistant service on the basis of an automatic translation call.

Provided are an apparatus and method for providing a personal assistant service based on automatic translation. The apparatus for providing a personal assistant service based on automatic translation includes an input section configured to receive a command of a user, a memory in which a program for providing a personal assistant service according to the command of the user is stored, and a processor configured to execute the program. The processor updates at least one of a speech recognition model, an automatic interpretation model, and an automatic translation model on the basis of an intention of the command of the user using a recognition result of the command of the user and provides the personal assistant service on the basis of an automatic translation call.

A discourse-level text translation method and device, the method comprising: acquiring a text to be translated, the text to be translated being a unit text in a discourse-level text to be translated (S101); acquiring an associated text of the text to be translated, the associated text including at least one of a preceding source text, a following source text, and a preceding target text (S102); and translating, according to the associated text, the text to be translated (S103).

A discourse-level text translation method and device, the method comprising: acquiring a text to be translated, the text to be translated being a unit text in a discourse-level text to be translated (S101); acquiring an associated text of the text to be translated, the associated text including at least one of a preceding source text, a following source text, and a preceding target text (S102); and translating, according to the associated text, the text to be translated (S103).