Translating terms using numeric representations

A method comprising:

• obtaining a plurality of training terms in a first language;
• identifying respective high-dimensional representations of the plurality of training terms;
• obtaining translations for the plurality of training terms, the translations being in a second language;
• identifying respective high-dimensional representations of the translations for the plurality of training terms;
• determining, by applying a machine learning technique to the high-dimensional representations of the training terms and the high-dimensional representations of the translations, trained values of transformation parameters that are used to transform a high-dimensional representation of a first term in the first language to a high-dimensional representation of a second term in the second language that is a translation of the first term, comprising:
• performing multiple iterations of a machine learning training procedure to determine a matrix of values W of the transformation parameters that satisfies:
• min
• W
• ⁢
• ∑
• i
• =
• 1
• n
• ⁢
• 
• 
• Wx
• i
• -
• z
• i
• 
• 
• 2
• ,
• wherein n is the total number of training terms, xi is the high-dimensional representation of an i-th training term, and zi is the high-dimensional representation of the translation of the i-th training term;
• and
• providing the trained values of the transformation parameters for use in translating a term in the first language to a term in the second language using a high-dimensional representation of the term in the first language and a high-dimensional representation of the term in the second language.

A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform system operations comprising:

• obtaining a plurality of training terms in a first language;
• identifying respective high-dimensional representations of the plurality of training terms;
• obtaining translations for the plurality of training terms, the translations being in a second language;
• identifying respective high-dimensional representations of the translations for the plurality of training terms;
• determining, by applying a machine learning technique to the high-dimensional representations of the training terms and the high-dimensional representations of the translations, trained values of transformation parameters that are used to transform a high-dimensional representation of a first term in the first language to a high-dimensional representation of a second term in the second language that is a translation of the first term, comprising:
• obtaining current values of the transformation parameters,
• processing, using the current values of the transformation parameters, each of the high-dimensional representations of one or more of the training terms to generate a respective high-dimensional representation of an output term for the training term,
• determining, for each of the one or more training terms, a respective difference between the high-dimensional representation of the translation for the training term and the high-dimensional representation of the output term for the training term, and
• modifying the current values of the transformation parameters to lower the respective differences;
• and
• providing the trained values of the transformation parameters for use in translating a term in the first language to a term in the second language using a high-dimensional representation of the term in the first language and a high-dimensional representation of the term in the second language.

A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising:

• obtaining a plurality of training terms in a first language;
• identifying respective high-dimensional representations of the plurality of training terms;
• obtaining translations for the plurality of training terms, the translations being in a second language;
• identifying respective high-dimensional representations of the translations for the plurality of training terms;
• determining, by applying a machine learning technique to the high-dimensional representations of the training terms and the high-dimensional representations of the translations, trained values of transformation parameters that are used to transform a high-dimensional representation of a first term in the first language to a high-dimensional representation of a second term in the second language that is a translation of the first term, comprising:
• performing multiple iterations of a machine learning training procedure to determine a matrix of values W of the transformation parameters that satisfies:
• min
• W
• ⁢
• ∑
• i
• =
• 1
• n
• ⁢
• 
• 
• Wx
• i
• -
• z
• i
• 
• 
• 2
• ,
• wherein n is the total number of training terms, xi is the high-dimensional representation of an i-th training term, and zi is the high-dimensional representation of the translation of the i-th training term;
• and
• providing the trained values of the transformation parameters for use in translating a term in the first language to a term in the second language using a high-dimensional representation of the term in the first language and a high-dimensional representation of the term in the second language.

A non-transitory computer-readable storage medium encoded with a computer program, the computer program comprising instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:

• obtaining a plurality of training terms in a first language;
• identifying respective high-dimensional representations of the plurality of training terms;
• obtaining translations for the plurality of training terms, the translations being in a second language;
• identifying respective high-dimensional representations of the translations for the plurality of training terms;
• determining, by applying a machine learning technique to the high-dimensional representations of the training terms and the high-dimensional representations of the translations, trained values of transformation parameters that are used to transform a high-dimensional representation of a first term in the first language to a high-dimensional representation of a second term in the second language that is a translation of the first term, comprising:
• obtaining current values of the transformation parameters,
• processing, using the current values of the transformation parameters, each of the high-dimensional representations of one or more of the training terms to generate a respective high-dimensional representation of an output term for the training term,
• determining, for each of the one or more training terms, a respective difference between the high-dimensional representation of the translation for the training term and the high-dimensional representation of the output term for the training term, and
• modifying the current values of the transformation parameters to lower the respective differences;
• and
• providing the trained values of the transformation parameters for use in translating a term in the first language to a term in the second language using a high-dimensional representation of the term in the first language and a high-dimensional representation of the term in the second language.

A non-transitory computer-readable storage medium encoded with a computer program, the computer program comprising instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:

• obtaining a plurality of training terms in a first language;
• identifying respective high-dimensional representations of the plurality of training terms;
• obtaining translations for the plurality of training terms, the translations being in a second language;
• identifying respective high-dimensional representations of the translations for the plurality of training terms;
• determining, by applying a machine learning technique to the high-dimensional representations of the training terms and the high-dimensional representations of the translations, trained values of transformation parameters that are used to transform a high-dimensional representation of a first term in the first language to a high-dimensional representation of a second term in the second language that is a translation of the first term, comprising:
• performing multiple iterations of a machine learning training procedure to determine a matrix of values W of the transformation parameters that satisfies:
• min
• W
• ⁢
• ∑
• i
• =
• 1
• n
• ⁢
• 
• 
• Wx
• i
• -
• z
• i
• 
• 
• 2
• ,
• wherein n is the total number of training terms, xi is the high-dimensional representation of an i-th training term, and zi is the high-dimensional representation of the translation of the i-th training term;
• and
• providing the trained values of the transformation parameters for use in translating a term in the first language to a term in the second language using a high-dimensional representation of the term in the first language and a high-dimensional representation of the term in the second language.