View source for 20240087561.USING SCENE-AWARE CONTEXT FOR CONVERSATIONAL AI SYSTEMS AND APPLICATIONS simplified abstract (nvidia corporation)

=USING SCENE-AWARE CONTEXT FOR CONVERSATIONAL AI SYSTEMS AND APPLICATIONS=


==Organization Name==

[[:Category:nvidia corporation|nvidia corporation]]


[[Category:nvidia corporation]]

==Inventor(s)==

[[:Category:Niral Lalit Pathak of San Jose CA (US)|Niral Lalit Pathak of San Jose CA (US)]][[Category:Niral Lalit Pathak of San Jose CA (US)]]

[[:Category:Rajath Shetty of Sunnyvale CA (US)|Rajath Shetty of Sunnyvale CA (US)]][[Category:Rajath Shetty of Sunnyvale CA (US)]]

[[:Category:Ratin Kumar of Cupertino CA (US)|Ratin Kumar of Cupertino CA (US)]][[Category:Ratin Kumar of Cupertino CA (US)]]

==USING SCENE-AWARE CONTEXT FOR CONVERSATIONAL AI SYSTEMS AND APPLICATIONS - A simplified explanation of the abstract==


This abstract first appeared for US patent application 20240087561 titled 'USING SCENE-AWARE CONTEXT FOR CONVERSATIONAL AI SYSTEMS AND APPLICATIONS

==Simplified Explanation==

The abstract describes techniques for using scene-aware context for dialogue systems and applications. Systems and methods are disclosed for processing audio data representing speech to determine intent, as well as processing sensor data to determine a point of interest associated with a user. The systems then generate a context associated with the point of interest and process the intent and context using language models to output data associated with the speech.

* Determining intent from audio data representing speech
* Processing sensor data to determine a point of interest associated with a user
* Generating context associated with the point of interest
* Processing intent and context using language models

== Potential Applications ==
The technology described in the patent application could be applied in various fields such as:
* Speech recognition systems
* Virtual assistants
* Augmented reality applications

== Problems Solved ==
The technology addresses the following issues:
* Improving accuracy in determining intent from speech
* Enhancing user experience by providing relevant context
* Integrating sensor data for more personalized interactions

== Benefits ==
The technology offers the following benefits:
* Enhanced dialogue systems
* Improved user engagement
* Personalized user experiences

== Potential Commercial Applications ==
The technology could be commercially applied in:
* Customer service chatbots
* Smart home devices
* Navigation systems

== Possible Prior Art ==
One possible prior art could be the use of language models in speech recognition systems. Another could be the integration of sensor data in user interfaces.

=== What are the specific language models used in processing intent and context? ===

The abstract mentions the use of one or more language models to process intent and context. However, it does not specify the exact language models utilized in the described systems and methods.

=== How does the technology differentiate between different points of interest within an environment? ===

While the abstract mentions determining a point of interest associated with a user, it does not elaborate on how the technology distinguishes between various points of interest, such as landmarks, people, or objects.


==Original Abstract Submitted==

in various examples, techniques for using scene-aware context for dialogue systems and applications are described herein. for instance, systems and methods are disclosed that process audio data representing speech in order to determine an intent associated with the speech. systems and methods are also disclosed that process sensor data representing at least a user in order to determine a point of interest associated with the user. in some examples, the point of interest may include a landmark, a person, and/or any other object within an environment. the systems and methods may then generate a context associated with the point of interest. additionally, the systems and methods may process the intent and the context using one or more language models. based on the processing, the language model(s) may output data associated with the speech.



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