Dialog Analysis Input Framing for User-Friendly AI Summaries
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Solution Overview
Problem
Users find it difficult to understand the content of analysis data relating to dialogues between multiple participants when presented with conventional analysis data.
Innovation Solution
An information processing apparatus that creates input data for a generative AI, such as a large-scale language model, to generate user-friendly responses based on analysis data from dialogues, using features like talk-to-listen ratio, overlap counts, silence duration, fundamental frequency, intonation, and language diversity indices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional analysis data is presented to users, then the data can be processed and analyzed, but users find it difficult to understand the content of the analysis data
Solution Approach 1:
The patent introduces an intermediary component (the server system with AI processing) that transforms complex analysis data into easily understandable information. The server acts as a mediator between the raw dialog analysis data and the user, converting technical metrics into meaningful insights through natural language generation and structured presentation.
Solution Approach 2:
The system changes the parameters of data presentation by transforming raw statistical metrics (talk-to-listen ratio, overlap counts, silence duration) into contextualized information with calculated indices (dialogue engagement index, information density index). This parameter transformation makes the data more comprehensible while preserving the underlying analytical value.
2Measurement precision
If detailed analysis data including multiple dialog features is provided, then comprehensive analysis is achieved, but user comprehension becomes difficult
Solution Approach 1:
The patent segments the comprehensive analysis data into distinct, manageable components. Each dialog feature (talk-to-listen ratio, overlap counts, silence duration, fundamental frequency, intonation, language diversity) is analyzed separately and then integrated through calculated indices. This segmentation allows precise measurement of individual features while presenting them in an organized, comprehensible manner.
Solution Approach 2:
The server system serves as an intermediary that processes detailed analysis data and transforms it into user-friendly presentations. The AI-based processing layer maintains measurement precision by accurately calculating multiple dialog features while simultaneously improving comprehension through natural language explanations and structured visual presentations.
3Reliability
If complex dialog features are analyzed, then thorough evaluation is possible, but the presentation becomes less accessible
Solution Approach 1:
The system performs parameter changes by calculating composite indices (dialogue engagement index, information density index) from multiple raw dialog features. This transformation maintains the reliability of thorough evaluation while improving accessibility by presenting results as meaningful indices with clear interpretations rather than raw statistical data.
Solution Approach 2:
The patent applies local quality by providing different levels of detail and presentation for different aspects of the analysis. The system maintains thorough evaluation through comprehensive feature analysis while improving accessibility by presenting tailored summaries and highlighted key insights that match user needs and comprehension levels.
Data Source
AI summary
An information processing apparatus for processing information on a dialog between a plurality of users, the apparatus includes processing circuitry configured to: acquire analysis data obtained by analyzing the dialog; and create input data to be input to a generative AI, based on the acquired analysis data.