View source for 20240021191. SYSTEMS AND METHODS FOR TRAINING A CONTROL SYSTEM BASED ON PRIOR AUDIO INPUTS simplified abstract (Rovi Guides, Inc.)

=SYSTEMS AND METHODS FOR TRAINING A CONTROL SYSTEM BASED ON PRIOR AUDIO INPUTS=


==Organization Name==

[[:Category:Rovi Guides, Inc.|Rovi Guides, Inc.]]


[[Category:Rovi Guides, Inc.]]

==Inventor(s)==

[[:Category:Bryan James of Davis CA (US)|Bryan James of Davis CA (US)]][[Category:Bryan James of Davis CA (US)]]

[[:Category:Manik Malhotra of Durham NC (US)|Manik Malhotra of Durham NC (US)]][[Category:Manik Malhotra of Durham NC (US)]]

==SYSTEMS AND METHODS FOR TRAINING A CONTROL SYSTEM BASED ON PRIOR AUDIO INPUTS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240021191 titled 'SYSTEMS AND METHODS FOR TRAINING A CONTROL SYSTEM BASED ON PRIOR AUDIO INPUTS

==Simplified Explanation==

The disclosed patent application describes systems and methods for training a control system using prior audio inputs. The system receives non-lexical or interjectional audio inputs and state change indications within a predefined period of time. It then receives a subsequent audio input and checks if it matches the previous audio input and if the contextual information also matches. If there is a match, the system stores a match association with a confidence factor in an associative data structure. If the confidence factor is above a certain threshold, the system executes one or more functions based on the stored state change indications.

* The patent application describes a system for training a control system based on prior audio inputs.
* The system receives non-lexical or interjectional audio inputs and state change indications.
* It stores the received audio inputs and state change indications within a predefined period of time.
* The system then receives a subsequent audio input and checks for a match with the previous audio input.
* If there is a match and the contextual information also matches, the system stores a match association with a confidence factor.
* If the confidence factor is above a preconfigured level, the system executes functions based on the stored state change indications.

Potential Applications:
* Voice-controlled systems: This technology can be applied to improve voice-controlled systems by training them to recognize and respond to specific audio inputs.
* Smart home automation: The control system can be trained to understand and execute commands based on audio inputs, enhancing the automation capabilities of smart homes.
* Virtual assistants: Virtual assistants can benefit from this technology by learning and adapting to user preferences and patterns in audio inputs.

Problems Solved:
* Improved accuracy: By training the control system based on prior audio inputs, the technology aims to improve the accuracy of recognizing and responding to specific audio inputs.
* Contextual understanding: The system considers contextual information to determine if the subsequent audio input matches the previous input, enabling a more accurate response.
* Efficient training: The system stores match associations with confidence factors, allowing for efficient training and execution of functions based on stored state change indications.

Benefits:
* Enhanced user experience: By accurately recognizing and responding to audio inputs, the technology can provide a more seamless and intuitive user experience.
* Personalization: The control system can be trained to adapt to individual users, providing personalized responses and improving overall satisfaction.
* Automation efficiency: With improved accuracy and contextual understanding, the control system can efficiently execute functions based on stored state change indications, enhancing automation efficiency.


==Original Abstract Submitted==

systems and methods are disclosed herein for training a control system based on prior audio inputs. the disclosed systems and methods receive a non-lexical or interjectional audio input. state change indications are also received and stored by the system within a predefined period of time starting from the time the system received the audio input. the system then receives a subsequent audio input. if the audio inputs of both the audio input and the subsequent audio input match, and contextual information for the audio input and the subsequent audio input match, the system stores a match association, comprising a confidence factor, for the subsequent audio input to the audio input in the associative data structure. if the confidence factor is greater than a preconfigured confidence level, the system executes one or more functions based on stored state change indications.



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