Dynamic Name and Acronym Resolution in Electronic Conferences
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Solution Overview
Problem
Electronic conferences often face challenges in understanding incomplete names and acronyms, leading to disruptions and increased bandwidth usage as participants search for clarifications.
Innovation Solution
A dynamic resolution system that identifies targets in speech, determines the closest vector based on usage context and stored information, and displays the most similar match to participants, thereby providing real-time clarification without disrupting the conference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If participants manually search for clarifications on incomplete names and acronyms, then understanding is improved, but bandwidth usage increases and conference flow is disrupted
Solution Approach 1:
The system performs preliminary resolution of incomplete names and acronyms by analyzing speech content in real-time, determining the most likely matches based on usage context and stored information before participants need to ask questions, thereby preventing information loss without requiring subsequent clarification exchanges that would consume bandwidth
2Loss of information
If participants manually search for clarifications on incomplete names and acronyms, then understanding is improved, but conference flow is disrupted
Solution Approach 1:
The system provides self-service by automatically resolving incomplete names and acronyms through contextual analysis and matching against stored information, eliminating the need for participants to interrupt the conference flow to seek clarifications, thus maintaining productivity while preventing information loss
3Measurement precision
If the system uses contextual analysis and stored information to resolve names and acronyms, then resolution accuracy is improved, but system complexity increases
Solution Approach 1:
The system employs a unified architecture that handles multiple functions including speech-to-text conversion, contextual analysis, information retrieval from stored data, vector-based matching, and result presentation through a single integrated platform, reducing overall system complexity while maintaining high resolution accuracy through multi-functional processing
Data Source
AI summary
At least one target in a speech of a first speaker during an electronic conference is identified. A closest vector between the identified target and a group of possible matches for the target is determined. A most similar match for the identified target is determined based on a current usage context for the identified target, a history of stored information associated with the first speaker and the identified target, and the determined closest vector. The most similar match to a set of participants of the electronic conference is displayed.