Invention Grant
- Patent Title: Global semantic word embeddings using bi-directional recurrent neural networks
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Application No.: US16111055Application Date: 2018-08-23
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Publication No.: US10984780B2Publication Date: 2021-04-20
- Inventor: Jerome R. Bellegarda
- Applicant: Apple Inc.
- Applicant Address: US CA Cupertino
- Assignee: Apple Inc.
- Current Assignee: Apple Inc.
- Current Assignee Address: US CA Cupertino
- Agency: Dentons US LLP
- Main IPC: G10L15/06
- IPC: G10L15/06 ; G10L15/18 ; G06N3/08 ; G10L15/30 ; G10L15/16

Abstract:
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.
Public/Granted literature
- US20190355346A1 GLOBAL SEMANTIC WORD EMBEDDINGS USING BI-DIRECTIONAL RECURRENT NEURAL NETWORKS Public/Granted day:2019-11-21
Information query