Encoding and adaptive, scalable accessing of distributed models
First Claim
Patent Images
1. A method for translating a text, comprising:
- receiving the text in a source language;
partitioning the text into a plurality of segments;
obtaining, for each segment, one or more candidate translations in a target language;
for each of a plurality of possible n grams in each candidate translation;
identifying a respective partition of a language model containing the n gram, wherein each partition includes a subset of all n grams in the target language and statistical data for the same subset of n grams, each n gram being a sequence of n tokens in the target language, wherein n is a positive integer, and wherein each partition is maintained by a different server of a plurality of servers;
sending a lookup request to the server maintaining the respective partition containing the n-gram;
obtaining, from the server maintaining the respective partition containing the n-gram, statistical data for the n gram; and
determining, for each segment of the text, a best candidate translation of the one or more candidate translations based on the obtained statistical data.
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Abstract
Systems, methods, and apparatus for accessing distributed models in automated machine processing, including using large language models in machine translation, speech recognition and other applications.
92 Citations
20 Claims
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1. A method for translating a text, comprising:
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receiving the text in a source language; partitioning the text into a plurality of segments; obtaining, for each segment, one or more candidate translations in a target language; for each of a plurality of possible n grams in each candidate translation; identifying a respective partition of a language model containing the n gram, wherein each partition includes a subset of all n grams in the target language and statistical data for the same subset of n grams, each n gram being a sequence of n tokens in the target language, wherein n is a positive integer, and wherein each partition is maintained by a different server of a plurality of servers; sending a lookup request to the server maintaining the respective partition containing the n-gram; obtaining, from the server maintaining the respective partition containing the n-gram, statistical data for the n gram; and determining, for each segment of the text, a best candidate translation of the one or more candidate translations based on the obtained statistical data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system comprising:
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a plurality of servers, wherein each server is configured to store a partition of a language model of a target language, wherein each respective partition of the language model includes a subset of all n grams in the target language and statistical data for the same subset of n grams, each n gram being a sequence of n tokens in the target language, and wherein n is a positive integer; and one or more processors configured to perform operations comprising; receiving a text in a source language; partitioning the text into a plurality of segments; obtaining, for each segment, one or more candidate translations in the target language; for each of a plurality of possible n grams in each candidate translation; identifying the respective partition of the language model containing the n gram; sending a lookup request to the server maintaining the respective partition containing the n-gram; obtaining, from the server maintaining the respective partition containing the n-gram, statistical data for the n gram; and determining, for each segment of the text, a best candidate translation of the one or more candidate translations based on the obtained statistical data. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. One or more computer storage media encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising:
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receiving a text in a source language; partitioning the text into a plurality of segments; obtaining, for each segment, one or more candidate translations in a target language; for each of a plurality of possible n grams in each candidate translation; identifying a respective partition of the language model containing the n gram, wherein each respective partition of the language model includes a subset of all n grams in the target language and statistical data for the same subset of n grams, each n gram being a sequence of n tokens in the target language, wherein n is a positive integer, and wherein each partition is maintained by a different server of a plurality of servers; sending a lookup request to the server maintaining the respective partition containing the n-gram; obtaining, from the server maintaining the respective partition containing the n-gram, statistical data for the n gram; and determining, for each segment of the text, a best candidate translation of the one or more candidate translations based on the obtained statistical data. - View Dependent Claims (19, 20)
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Specification