Google LLC (20240328807). CONTEXT AWARE NAVIGATION VOICE ASSISTANT simplified abstract
Contents
CONTEXT AWARE NAVIGATION VOICE ASSISTANT
Organization Name
Inventor(s)
Migle Padegimaite of Mountain View CA (US)
Sammy El Ghazzal of Mountain View CA (US)
CONTEXT AWARE NAVIGATION VOICE ASSISTANT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240328807 titled 'CONTEXT AWARE NAVIGATION VOICE ASSISTANT
Simplified Explanation: The patent application describes a system that uses machine learning to provide context-aware audio navigation instructions to users based on their environment.
- Machine Learning Model: Trains a model using previous audio navigation instructions, sensor data, and user responses to identify parameters for specific contexts.
- Sensor Data Integration: Receives sensor data from a user's device to understand the surrounding environment and generate personalized audio navigation instructions.
- Responsive Instructions: Generates and provides tailored audio navigation instructions to the user based on the received sensor data and machine learning model.
- Enhanced User Experience: Improves the accuracy and relevance of audio navigation instructions by considering the user's context in real-time.
- Efficient Navigation: Helps users navigate more effectively by providing instructions that are specific to their current environment.
Potential Applications: This technology can be applied in various industries such as transportation, tourism, and outdoor activities to enhance navigation experiences for users.
Problems Solved: This technology addresses the challenge of providing personalized and context-aware audio navigation instructions to users in real-time.
Benefits: - Improved accuracy and relevance of navigation instructions - Enhanced user experience with personalized guidance - Efficient navigation in various environments
Commercial Applications: Title: Context-Aware Audio Navigation System for Enhanced User Experience This technology can be utilized in navigation apps, smart vehicles, and location-based services to offer personalized audio guidance to users, improving their overall navigation experience.
Prior Art: Further research can be conducted in the field of context-aware navigation systems and machine learning models for personalized user experiences.
Frequently Updated Research: Researchers are continuously exploring advancements in machine learning algorithms for context-aware applications and personalized user interactions.
Questions about Context-Aware Audio Navigation Systems: 1. How does the integration of sensor data improve the accuracy of audio navigation instructions? 2. What are the potential privacy concerns associated with collecting and analyzing user sensor data for context-aware navigation systems?
Original Abstract Submitted
to provide context-aware audio navigation instructions, a server device obtains sets of audio navigation instructions previously provided to users along with sensor data descriptive of a context in which the audio navigation instructions were provided and an indication of whether a driver correctly responded to the audio navigation instructions. the server device trains a machine learning model using this data, where the machine learning model identifies audio navigation instruction parameters for a particular context. in response to a request for navigation directions, the server device receives sensor data from the client computing device generating the request that is indicative of the environment surrounding the client computing device. the server device then applies the sensor data and navigation instructions to the machine learning model to generate a set of audio navigation instructions responsive to the request. the server device provides the set of audio navigation instructions to the client computing device.
