EFFICIENT WORD ENCODING FOR RECURRENT NEURAL NETWORK LANGUAGE MODELS

Patent №

US 10,366,158

Granted

2019-07-30

Filed 2016

Owner

APPLE INC.

Lab

AI components

4

ml · nlp · speech · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15141660

Systems and processes for efficient word encoding are provided. In accordance with one example, a method includes, at an electronic device with one or more processors and memory, receiving a user input including a word sequence, and providing a representation of a current word of the word sequence. The representation of the current word may be indicative of a class of a plurality of classes and a word associated with the class. The method further includes determining a current word context based on the representation of the current word and a previous word context, and providing a representation of a next word of the word sequence. The representation of the next word of the word sequence may be based on the current word context. The method further includes displaying, proximate to the user input, the next word of the word sequence.

Machine learningNatural languageSpeechAI hardwareG06F 40/274G06F 16/353G06N 3/02G06N 3/044G06N 3/0442G06N 5/022G10L 15/16G10L 15/183

AI classification

Natural language1.00
Speech1.00
AI hardware1.00
Machine learning0.90
Vision0.33
Knowledge representation0.16
Evolutionary computation0.14
Planning0.00

Ownership

APPLE INC.

assignment · 384880751

Assignors

BELLEGARDA, JEROME R., DOLFING, JANNES G.

On an employer assignment, the assignors are typically the inventors.

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