Multi-task recurrent neural network architecture for efficient morphology handling in neural language modeling

  • US 10,657,328 B2
  • Filed: 12/21/2017
  • Issued: 05/19/2020
  • Est. Priority Date: 06/02/2017
  • Status: Active Grant
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First Claim
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1. An electronic device, comprising:

  • one or more processors;

    a memory; and

    one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for;

    receiving a current word;

    determining a context of the current word based on the current word and a context of a previous word;

    determining, using a morpheme-based language model, a first representation indicating a likelihood of each prefix of a predetermined set of prefixes, wherein the likelihood of each prefix is determined based on the context of the current word;

    determining, using the morpheme-based language model, a second representation indicating a likelihood of each stem of a predetermined set of stems, wherein the likelihood of each stem is determined based on the context of the current word;

    determining, using the morpheme-based language model, a third representation indicating a likelihood of each suffix of a predetermined set of suffixes, wherein the likelihood of each suffix is determined based on the context of the current word;

    determining a next word based on the first representation, the second representation, and the third representation; and

    providing an output including the next word.

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