Conversational System Context Awareness via Sensor Merging
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Solution Overview
Problem
Conversational systems lack the ability to gather and utilize context information from user devices, limiting their understanding of user preferences, habits, and emotions, and fail to provide enhanced communication methods beyond traditional text or speech.
Innovation Solution
The use of sensors on user devices to gather context information, combined with graphical user interfaces (GUIs) that allow users to specify semantic information and alter response attributes, and the provision of haptic or audio feedback to convey emotions and additional information during conversational sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional communication methods (text/speech) are used for conversational exchange, then the system is simple to operate, but the system lacks the ability to gather and utilize context information from user devices
Solution Approach 1:
The patent merges the conversational system with the user device's sensor system, allowing the system to access and process context information from sensors such as accelerometers, gyroscopes, and microphones. This integration enables the system to gather information about user behavior, environment, and device usage patterns without requiring a completely separate information gathering system.
Solution Approach 2:
The patent makes the user device serve multiple functions: it acts as both the communication interface and the context information gathering system. The sensors originally designed for other purposes (motion detection, ambient light sensing) are repurposed to provide context information for the conversational system, eliminating the need for dedicated specialized hardware.
2Measurement precision
If sensors are used to gather context information, then the system gains deeper understanding of user preferences and habits, but the device complexity increases
Solution Approach 1:
The system processes and interprets sensor data automatically without requiring manual user input or configuration. The conversational system self-adjusts based on the context information gathered from sensors, such as automatically detecting user activity states or environmental conditions and adapting its behavior accordingly, reducing the need for complex manual setup.
Solution Approach 2:
The system continuously monitors and pre-processes sensor data in the background before conversational interactions occur. By maintaining an ongoing understanding of user context through continuous sensor monitoring, the system is prepared to provide more accurate and personalized responses without requiring complex real-time processing during the actual conversation.
3Loss of information
If haptic or audio feedback is provided to convey emotion, then enhanced communication is achieved, but the use of energy increases
Solution Approach 1:
The system provides haptic or audio feedback selectively rather than continuously, using these energy-consuming channels only when appropriate for conveying emotional or contextual information. The system judiciously chooses when to activate additional feedback mechanisms based on the conversational context, providing enhanced communication only when beneficial rather than constantly consuming additional energy.
4Ease of operation
If GUI with skeuomorphic elements is used to allow user specification of semantic information, then ease of operation improves, but device complexity increases
Solution Approach 1:
The skeuomorphic GUI elements replicate familiar real-world objects and interfaces (such as physical knobs, sliders, or buttons) in the digital interface. This copying of familiar physical forms into the digital domain allows users to interact with abstract semantic parameters using intuitive, physically-inspired controls, reducing the cognitive load required to understand and manipulate the interface.
Data Source
AI summary
Examples of the present disclosure describe systems and methods relating to conversational system user experience. In an example, a conversational system may use one or more sensors of a user device to affect the topic or direction of a conversation or to identify a new conversation topic. The conversational system may also receive input from a user, wherein a GUI may enable the user to specify or alter semantic information used during the conversation. The GUI may comprise one or more skeuomorphic elements designed to provide a familiar or intuitive way for the user to interact with the conversational system. The GUI may also be used to disambiguate messages or convey emotion or sentiment to the user. In another example, haptic or audio feedback may be provided alongside a message to convey emotion to the user during the conversation.