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US 11,893,994 B1Granted
Processing optimization using machine learning
AssigneeAmazon Technologies, Inc.
InventorsSamuel Tucker, Agnika Kumar, Brett James Panosh
Life of this patent
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Abstract
Devices and techniques are generally described for process optimization using reinforcement learning. In various examples, first input data is received and a first process for processing the first input data is determined. In some examples, a second process for processing the first input data is determined. A first machine learning model is used to generate a first prediction for processing the first input data by the first process. The first process and/or the second process are controlled based at least in part on the first prediction.
Claims20
A computer-implemented method, comprising:
- receiving first audio data representing a user request by a speech processing-enabled device;
- generating, by an automatic speech recognition (ASR) component, first text data representing the user request;
- determining a first natural language understanding (NLU) process to process the first text data to determine a first semantic interpretation of the first text data using a first set of NLU processing actions associated with the first NLU process;
- determining a second NLU process for processing the first text data to determine a second semantic interpretation of the first text data using a second set of NLU processing actions associated with the second NLU process;
- executing the first NLU process, comprising:
- generating first intermediate NLU result data;
- and
- generating first feature data from the first intermediate NLU result data;
- executing the second NLU process in parallel with executing the first NLU process, comprising:
- generating second intermediate NLU result data;
- and
- generating second feature data from the second intermediate NLU result data;
- inputting the first feature data and the second feature data into a reinforcement machine learning model;
- determining, by the reinforcement machine learning model using the first feature data and the second feature data, that the first NLU process is preferred with respect to the second NLU process based on at least one of first accuracy characteristics or first latency characteristics of the first NLU process and based on at least one of second accuracy characteristics or second latency characteristics of the second NLU process;
- determining at least one updated parameter of the reinforcement machine learning model using a reward function;
- determining a first final result from the first NLU process;
- and
- terminating the second NLU process.
15 more elements
A method comprising:
- receiving first input data by a speech processing system;
- executing a first natural language understanding (NLU) process for processing the first input data, wherein the first NLU process comprises a first set of NLU processing actions;
- executing a second NLU process for processing the first input data, wherein the second NLU process comprises a second set of NLU processing actions different from the first set of NLU processing actions;
- determining, using a first machine learning model, a first recommended action for processing the first input data by the first NLU process, wherein the first recommend action is effective to optimize at least one of the first NLU process or the second NLU process based on at least one of latency, accuracy, or performance;
- and
- sending the first recommended action to a natural language processing component executing at least one of the first NLU process or the second NLU process.
3 more elements
A computing device, comprising:
- at least one processor;
- and
- at least one non-transitory computer-readable memory storing instructions that, when executed by the at least one processor, program the at least one processor to:
- receive first input data by a speech processing system;
- execute a first natural language understanding (NLU) process for processing the first input data, wherein the first NLU process comprises a first set of NLU processing actions;
- execute a second NLU process for processing the first input data, wherein the second NLU process comprises a second set of NLU processing actions different from the first set of NLU processing actions;
- determine, using a first machine learning model, a first recommended action for processing the first input data by the first NLU process, wherein the first recommend action is effective to optimize at least one of the first NLU process or the second NLU process based on at least one of latency, accuracy, or performance;
- and
- send the first recommended action to a natural language processing component executing at least one of the first NLU process or the second NLU process.
6 more elements
Dependencies are inferred from the claim text.