DIGITAL ASSISTANT AND ASSOCIATED METHODS FOR A TRANSPORTATION VEHICLE
First Claim
1. A method comprising:
- training a neural network for an action category on an aircraft associated with an intended user request by defining at least a filter parameter and a response context based on the filter parameter;
generating by the neural network an action context based on the action category, a filter context and a response context for a tagged user input;
using a short term memory configured as a least recently used memory for storing a key-value pair associated with the filter parameter of the filter context;
generating an output by the neural network in response to a follow-up request from the user;
updating the key-value pair at the short term memory based on the output from the neural network; and
providing a response to the follow-up request.
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Abstract
Methods and systems for a transportation vehicle are provided. One method includes receiving a user input for a valid communication session by a processor executable, digital assistant at a device on a transportation vehicle; tagging by the digital assistant, the user input words with a grammatical connotation; generating an action context, a filter context and a response context by a neural network, based on the tagged user input; storing by the digital assistant, a key-value pair for a parameter of the filter context at a short term memory, based on an output from the neural network; updating by the digital assistant, the key-value pair at the short term memory after receiving a reply to a follow-up request and another output from the trained neural network; and providing a response to the reply by the digital assistant.
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Citations
20 Claims
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1. A method comprising:
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training a neural network for an action category on an aircraft associated with an intended user request by defining at least a filter parameter and a response context based on the filter parameter; generating by the neural network an action context based on the action category, a filter context and a response context for a tagged user input; using a short term memory configured as a least recently used memory for storing a key-value pair associated with the filter parameter of the filter context; generating an output by the neural network in response to a follow-up request from the user; updating the key-value pair at the short term memory based on the output from the neural network; and providing a response to the follow-up request. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A method comprising:
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training a neural network for an action category on an aircraft associated with an intended user request by defining at least a filter parameter and a response context based on the filter parameter; generating by the neural network an action context that maps to an action application programming interface (API) based on the action category, a filter context and a response context for a tagged user input, wherein the tagged user input is a user input transformed by a tag indicating a grammatical connotation; wherein the action context identifies a type of action associated with the action category, the filter context defines one or more filter parameters that define a query parameter for the action API, and the response context provides information to extract from the action context to execute an action; using a short term memory configured as a least recently used memory for storing a key-value pair associated with one or more of the filter parameters of the filter context and any missing parameter for the action API for a most current action context of a user session; generating an output by the neural network in response to a follow-up request for the user session; updating the key-value pair at the short term memory based on the output from the neural network; and providing a response to the follow-up request. - View Dependent Claims (9, 10, 11, 12, 13, 14)
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15. A non-transitory machine-readable storage medium having stored thereon instructions for performing a method comprising machine executable code, which when executed by at least one machine, causes the machine to:
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train a neural network for an action category on an aircraft associated with an intended user request by defining at least a filter parameter and a response context based on the filter parameter; generate by the neural network an action context that maps to an action application programming interface (API) based on the action category, a filter context and a response context for a tagged user input, wherein the tagged user input is a user input transformed by a tag indicating a grammatical connotation; wherein the action context identifies a type of action associated with the action category, the filter context defines one or more filter parameters that define a query parameter for the action API, and the response context provides information to extract from the action context to execute an action; use a short term memory configured as a least recently used memory for storing a key-value pair associated with one or more of the filter parameter of the filter context and any missing parameter for the action API for a most current action context of a user session; generate an output by the neural network in response to a follow-up request for the user session; update the key-value pair at the short term memory based on the output from the neural network; and provide a response to the follow-up request. - View Dependent Claims (16, 17, 18, 19, 20)
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Specification