Voice Recognition Terminal for Active Conversation Information Extraction
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Solution Overview
Problem
Existing voice recognition services in smartphones are limited to passive operations based on user commands, failing to actively extract and provide relevant information from telephone conversations, such as schedules, contacts, and app-related data.
Innovation Solution
A system that analyzes telephone conversation content using voice recognition to actively extract and provide information on schedules, contacts, and app-related data, allowing for automatic matching and display of relevant information during or after calls, including app execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If existing voice recognition services are used for passive operations based on user commands, then the services can execute simple commands like app execution or web surfing, but the services cannot actively extract and provide relevant information from telephone conversations such as schedules, contacts, and app-related data
Solution Approach 1:
The system performs preliminary actions by continuously monitoring telephone conversations and pre-extracting relevant information (schedules, contacts, app data) before the user needs it. The voice recognition system analyzes conversation content in advance and prepares extracted information for automatic provision to the user, eliminating the need for manual information gathering during actual use.
Solution Approach 2:
The voice recognition service performs self-service by automatically analyzing telephone conversations and extracting relevant information without requiring explicit user commands. The system serves itself by proactively identifying and preparing information that the user may need, then automatically providing it through the terminal, reducing the burden on the user to manually request information.
2Productivity
If the system analyzes telephone conversation content using voice recognition to actively extract information, then relevant information can be automatically provided to the user, but additional processing time and computational resources are required
Solution Approach 1:
The system maintains continuous useful action by continuously monitoring telephone conversations and extracting relevant information in real-time. Rather than processing information only when requested, the system operates continuously during conversations, immediately identifying and preparing useful information as it becomes available, thereby reducing overall processing time and improving productivity.
Solution Approach 2:
The system applies extraction by isolating and separating relevant information (schedules, contacts, app data) from the broader context of telephone conversations. The voice recognition system extracts only the useful portions of conversation content, filtering out unnecessary information, which improves processing efficiency by focusing computational resources only on extracting meaningful data rather than processing entire conversations.
3Ease of operation
If the system extracts and provides information automatically during or after calls, then user convenience is enhanced, but the system requires integration with multiple functions including schedule management, contact storage, and app execution
Solution Approach 1:
The system achieves universality by integrating multiple functions into a single unified platform. The terminal and server work together to provide voice recognition, information extraction, schedule management, contact storage, and app execution capabilities through one cohesive system. This multi-functional approach enhances user convenience while managing integration complexity through centralized processing architecture.
Solution Approach 2:
The server acts as an intermediary between the terminal and various system functions. Rather than requiring direct integration of all functions within the terminal, the server mediates by receiving conversation data from the terminal, processing information extraction, and then providing relevant information back to the terminal for execution. This intermediary approach simplifies terminal complexity while maintaining comprehensive functionality.
Data Source
AI summary
A terminal for actively providing information based on communication contents of a communication session. The terminal comprises a display unit that divides at least one of a schedule, Apps, REC, information regarding a matter of interest, and a contact into categories and displays, according to the categories, at least one of information regarding a communicator's matter of interest, schedule-related information, address book information corresponding to name information within a subscriber address book, first information relating to Apps within the subscriber terminal, and one or more App driving icons corresponding to the first information that are extracted from communication contents for at least one of a subscriber and a communication opponent in the communication session.