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US Patent 10210862 Lattice decoding and result confirmation using recurrent neural networks

Patent 10210862 was granted and assigned to Amazon on February, 2019 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
Amazon
Amazon
1
Current Assignee
Amazon
Amazon
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
102108621
Patent Inventor Names
Markus Dreyer1
Björn Hoffmeister1
Faisal Ladhak1
Lambert Mathias1
Ankur Gandhe1
Ariya Rastrow1
Date of Patent
February 19, 2019
1
Patent Application Number
150918711
Date Filed
April 6, 2016
1
Patent Citations Received
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US Patent 11914678 Input encoding for classifier generalization
2
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US Patent 10657955 Systems and methods for principled bias reduction in production speech models
‌
US Patent 11688394 Entity language models for speech processing
5
Patent Primary Examiner
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Michael Ortiz-Sanchez
1
Patent abstract

Neural networks may be used in certain automatic speech recognition systems. To improve performance at these neural networks, the present system converts the lattice into a matrix form, thus maintaining certain information included in the lattice that might otherwise be lost while also placing the lattice in a form that may be manipulated by other components to perform operations such as checking ASR results. The matrix representation of the lattice may be transformed into a vector representation by calculations performed at a recurrent neural network (RNN). By representing the lattice as a vector representation the system may perform additional operations, such as ASR results confirmation.

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