Interaction Data Generation via Coupling Contexts
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Solution Overview
Problem
Generating high-performance interaction agents requires substantial manpower, time, and cost due to the need for extensive interaction data collection and customization of interaction scenarios.
Innovation Solution
An information processing device and method that generate interaction data by creating a coupling context based on interaction history information, allowing for the integration and utilization of multiple interaction histories to produce interaction transitions with reduced costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If interaction data is collected manually and interaction scenarios are customized for particular purposes, then the quality and performance of interaction agents is improved, but the cost and time required increases significantly
Solution Approach 1:
The patent applies copying by generating interaction data through automatic generation processes that replicate and adapt existing interaction patterns from interaction history information, rather than manually collecting each interaction scenario. This allows multiple interaction scenarios to be created by copying and transforming proven interaction patterns, significantly reducing the time and cost of data collection while maintaining quality through systematic reuse of effective interaction templates
Solution Approach 2:
The patent applies preliminary action by pre-processing interaction history information to extract and structure reusable interaction patterns and contexts before they are needed for generating new interaction data. This advance preparation creates a library of validated interaction templates that can be quickly assembled and customized for specific purposes, eliminating the need for time-consuming manual collection and customization of each interaction scenario
2Reliability
If sufficient interaction data is collected and customized interaction scenarios are generated, then high-performance interaction agents can be created, but the cost increases hugely
Solution Approach 1:
The patent applies universality by creating a multi-functional automatic generation system that handles multiple types of interaction data generation tasks using a unified process. The system generates various interaction scenarios, contexts, and patterns through a single automated framework that adapts to different purposes and domains, eliminating the need for separate manual customization processes for each interaction type and significantly reducing overall generation costs
Solution Approach 2:
The patent applies parameter changes by systematically varying parameters such as interaction contexts, scenarios, and configurations through automatic generation algorithms. Instead of manually creating each unique interaction scenario, the system changes key parameters of base interaction patterns to generate diverse, purpose-specific interaction data, reducing costs while maintaining the quality and variety needed for high-performance interaction agents
3Manufacturing precision
If manual methods are used to collect and customize interaction data, then data quality can be controlled, but the complexity and resource requirements increase
Solution Approach 1:
The patent applies self-service by enabling the interaction data generation system to automatically validate, verify, and quality-check its own generated output through built-in evaluation mechanisms. The system autonomously assesses the quality and appropriateness of generated interaction data against predefined criteria and interaction history patterns, eliminating the need for complex manual review processes while maintaining consistent quality control across all generated data
Data Source
AI summary
The present technology relates to an information processing device and an information processing method that make it possible to generate interaction data with less cost.Provided is the information processing device including a processor that generates, on the basis of interaction history information, a coupling context to be coupled to a context of interest to be noticed among a plurality of contexts. This makes it possible to generate interaction data with less cost. The present technology is applicable as server-side service of a voice interaction system, for example.