首页> 外国专利> GLOBAL SEMANTIC WORD EMBEDDINGS USING BI-DIRECTIONAL RECURRENT NEURAL NETWORKS

GLOBAL SEMANTIC WORD EMBEDDINGS USING BI-DIRECTIONAL RECURRENT NEURAL NETWORKS

机译:使用双向递归神经网络的全球语义词嵌入

摘要

Systems and processes for operating a digital assistant are provided. In accordance with one or more examples, a method includes, receiving training data for a data-driven learning network. The training data include a plurality of word sequences. The method further includes obtaining representations of an initial set of semantic categories associated with the words included in the training data; and training the data-driven learning network based on the plurality of word sequences included in the training data and based on the representations of the initial set of semantic categories. The training is performed using the word sequences in their entirety. The method further includes obtaining, based on the trained data-driven learning network, representations of a set of semantic embeddings of the words included in the training data; and providing the representations of the set of semantic embeddings to at least one of a plurality of different natural language processing tasks.
机译:提供了用于操作数字助理的系统和过程。根据一个或多个示例,一种方法包括:接收用于数据驱动的学习网络的训练数据。训练数据包括多个单词序列。该方法进一步包括获得与训练数据中包括的单词相关联的语义类别的初始集合的表示;基于训练数据中包括的多个单词序列并基于语义类别的初始集合的表示来训练数据驱动的学习网络。使用整个单词序列来执行训练。该方法进一步包括:基于训练后的数据驱动的学习网络,获得训练数据中包括的单词的语义嵌入集合的表示;以及将语义嵌入集合的表示提供给多个不同自然语言处理任务中的至少一个。

著录项

  • 公开/公告号US2019355346A1

    专利类型

  • 公开/公告日2019-11-21

    原文格式PDF

  • 申请/专利权人 APPLE INC.;

    申请/专利号US201816111055

  • 发明设计人 JEROME R. BELLEGARDA;

    申请日2018-08-23

  • 分类号G10L15/06;G10L15/18;G10L15/16;G10L15/30;G06N3/08;

  • 国家 US

  • 入库时间 2022-08-21 11:20:30

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