Dynamic Topic Management for Natural Language Conversations
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Solution Overview
Problem
Existing voice-enabled consumer devices are limited in maintaining meaningful conversations with users, providing only short and mechanical responses, and are unable to deliver substantive interactions beyond basic exchanges.
Innovation Solution
A computing device with a program module that manages conversations by identifying and prioritizing topics, dynamically accessing contextual information to generate contextually relevant responses, and adjusting topic priorities based on user inputs and events, allowing for natural and dynamic natural language interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If existing voice-enabled systems translate user voice to invoke actions, then basic commands can be executed, but the conversation feels mechanical and unnatural
Solution Approach 1:
The patent segments the conversation into multiple topics with different priorities. Instead of treating the entire interaction as a single transactional exchange, the system divides it into manageable topic units (e.g., gaming topic, music topic, weather topic) that can be independently tracked and managed, allowing for more natural conversational flow while maintaining operational efficiency
Solution Approach 2:
The patent implements dynamic topic prioritization where topic priorities change over time based on user input and contextual factors. Topics are not static but evolve dynamically, with the system able to elevate certain topics when relevant and let others fade, creating a more adaptive and natural conversation experience rather than rigid mechanical responses
2Productivity
If voice-enabled systems provide short translated responses, then processing speed is maintained, but substantive interaction is limited
Solution Approach 1:
The patent performs preliminary actions by proactively introducing topics and maintaining contextual information before users explicitly request it. The system anticipates user needs by pre-loading relevant contextual data and introducing related topics, reducing the need for lengthy back-and-forth exchanges while maintaining rich contextual understanding
Solution Approach 2:
The patent introduces topics as intermediary structures that mediate between the user's brief input and the system's response generation. These topics serve as contextual containers that hold and organize information, allowing the system to access rich contextual depth without requiring proportionally longer processing time or user input
3Reliability
If the system manages multiple topics dynamically, then conversation naturalness improves, but system complexity increases
Solution Approach 1:
The patent uses simplified topic data structures that copy essential contextual information rather than maintaining complex hierarchical relationships. Each topic is represented as a manageable unit with key attributes (priority, relevance score, associated data), allowing the system to track multiple topics without proportionally increasing complexity
Solution Approach 2:
The patent manages topic complexity by dynamically changing parameters such as topic priority levels and relevance scores rather than maintaining fixed complex structures. The system adjusts these parameters based on user input and contextual factors, allowing flexible topic management with relatively simple data structures that adapt to conversation needs
Data Source
AI summary
Technologies are described herein for providing dynamic natural language interactions between a user and a computing device. In one aspect, a computing device managing a conversation with a user is enhanced with the identification and management of one or more topics. Using techniques described herein, the computing device can focus on one or more topics, shift between topics and/or introduce new topics. Techniques disclosed herein may also manage and process interruptions that may be introduced during a conversation. Dynamic access of contextual information may assist in the generation of contextually-relevant statements, and the contextual information may be used to balance priorities between various topics. Each topic may also have an associated decay rate so that the lifespan of individual topics may track realistic scenarios. In addition, the priorities of individual topics may be dynamically adjusted so topics may track events created by a user and a computing device.