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US Patent 11676579 Deep learning internal state index-based search and classification

Patent 11676579 was granted and assigned to DeepGram on June, 2023 by the United States Patent and Trademark Office.

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Is a
Patent
Patent
1

Patent attributes

Patent Applicant
DeepGram
DeepGram
1
Current Assignee
DeepGram
DeepGram
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
116765791
Date of Patent
June 13, 2023
1
Patent Application Number
170731491
Date Filed
October 16, 2020
1
Patent Citations
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US Patent 9519859 Deep structured semantic model produced using click-through data
1
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US Patent 9524716 Systems and methods for providing unnormalized language models
1
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US Patent 9595002 Normalizing electronic communications using a vector having a repeating substring as input for a neural network
1
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US Patent 9620145 Context-dependent state tying using a neural network
1
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US Patent 9646634 Low-rank hidden input layer for speech recognition neural network
1
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US Patent 9824692 End-to-end speaker recognition using deep neural network
1
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US Patent 9842585 Multilingual deep neural network
1
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US Patent 9916538 Method and system for feature detection
1
...
Patent Citations Received
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US Patent 12080283 Multilingual re-scoring models for automatic speech recognition
2
Patent Primary Examiner
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Jonathan C Kim
1

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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