Contextual Natural-Language Query Generation for Transcript Search
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The challenge of efficiently searching through large volumes of virtual meeting or presentation recordings due to the cumbersome nature of transcripts and the inefficiency of exact-match keyword queries, leading to wasted time and computing resources.
Innovation Solution
Surfacing relevant natural language queries based on input signals generated during or from the meeting, using heuristics or a trained machine-learning model to generate personalized, contextual search queries that are presented in real-time or post-meeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If exact-match keyword queries are used to search transcripts, then users can perform simple searches, but the search results are often less useful and require reviewing entire meeting recordings
Solution Approach 1:
The system transforms the search parameter from exact-match keywords to semantic concepts and natural language queries. By changing the search parameter type, the system enables users to search using meaningful phrases and concepts rather than requiring precise keyword matching, thereby improving information retrieval effectiveness while maintaining ease of operation
Solution Approach 2:
The patent replaces the mechanical keyword-matching system with a semantic search system that uses natural language processing and machine learning. This substitution allows the system to understand the meaning and context of search queries rather than merely matching exact keywords, resolving the contradiction between simple search operations and effective information retrieval
2Reliability
If users review entire meeting recordings to find information, then comprehensive search is performed, but significant time is wasted
Solution Approach 1:
The system extracts and surfaces relevant natural language queries from the meeting transcript automatically. By extracting key questions and topics directly from the conversation, the system allows users to jump directly to relevant sections without reviewing entire recordings, maintaining search completeness while dramatically reducing time to locate information
Solution Approach 2:
The system performs preliminary analysis of the meeting transcript to generate and surface relevant search queries before the user needs to search. By pre-processing the transcript to identify key topics, questions, and relevant sections, the system prepares the information in advance, enabling users to quickly find what they need without comprehensive review
3Loss of information
If semantic natural-language queries are used for searching transcripts, then more useful results are obtained, but system complexity increases
Solution Approach 1:
The system automatically generates relevant natural language search queries from the meeting transcript itself without requiring complex user input or configuration. By having the system serve itself in creating search queries based on the content it already processed, it achieves effective information retrieval while keeping the user interface simple and the overall system complexity manageable
Data Source
AI summary
Systems and methods for surfacing natural language queries from one or more transcripts. An example method may include converting received audio to text, through automated speech recognition, to form a transcript of the audio, wherein the transcript includes text of the audio and identifications of speakers associated with portions of the text corresponding to utterances from the respective speakers; generating input signals based on at least the transcript; executing at least one of one or more heuristics or a trained machine-learning (ML) model, using the generated input signals as an input, to generate at least one of a suggested natural language query for searching the transcript or a key moment within the received audio; and causing at least one of the suggested natural language query or the key moment to be surfaced on one or more remote devices.