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US Patent 10380997 Deep learning internal state index-based search and classification

Patent 10380997 was granted and assigned to DeepGram on August, 2019 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
DeepGram
DeepGram
Current Assignee
DeepGram
DeepGram
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10380997
Patent Inventor Names
Jeff Ward0
Scott Stephenson0
Adam Sypniewski0
Date of Patent
August 13, 2019
Patent Application Number
16108109
Date Filed
August 22, 2018
Patent Citations
‌
US Patent 10170107 Extendable label recognition of linguistic input
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US Patent 10089580 Generating and using a knowledge-enhanced model
0
Patent Citations Received
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US Patent 11869507 Methods, systems and apparatuses for improved speech recognition and transcription
0
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US Patent 11514311 Automated data slicing based on an artificial neural network
0
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US Patent 11551694 Methods, systems and apparatuses for improved speech recognition and transcription
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US Patent 11562733 Deep learning models for speech recognition
0
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US Patent 10839792 Recognition of out-of-vocabulary in direct acoustics-to-word speech recognition using acoustic word embedding
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US Patent 10997966 Voice recognition method, device and computer storage medium
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US Patent 11496775 Neural network model compression with selective structured weight unification
Patent Primary Examiner
‌
Jonathan C Kim
Patent abstract

Systems and methods are disclosed for generating internal state representations of a neural network during processing and using the internal state representations for classification or search. In some embodiments, the internal state representations are generated from the output activation functions of a subset of nodes of the neural network. The internal state representations may be used for classification by training a classification model using internal state representations and corresponding classifications. The internal state representations may be used for search, by producing a search feature from an search input and comparing the search feature with one or more feature representations to find the feature representation with the highest degree of similarity.

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