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Global semantic word embeddings using bi-directional recurrent neural networks

机译:使用双向反复性神经网络嵌入全局语义词

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,一种方法包括接收数据驱动学习网络的训练数据。训练数据包括多个单词序列。该方法还包括获取与培训数据中包括的单词相关联的初始语义类别的表示;并基于培训数据中包括的多个单词序列训练数据驱动学习网络,并基于初始语义类别的表示。培训以整体使用单词序列进行。该方法还包括基于训练有素的数据驱动学习网络,从而获得训练数据中包括的单词的一组语义嵌入的表示;并向多个不同的自然语言处理任务中的至少一个提供该组语义嵌入的表示。

著录项

  • 公开/公告号US10984780B2

    专利类型

  • 公开/公告日2021-04-20

    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;G06N3/08;G10L15/30;G10L15/16;

  • 国家 US

  • 入库时间 2022-08-24 18:17:03

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