Meeting Assistant Speech Recognition Enterprise Data
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Solution Overview
Problem
In-person meetings face challenges with real-time data retrieval due to the limitations of participants' agility in identifying and accessing relevant information, which can hinder the pace of interaction and idea exchange.
Innovation Solution
A method and system for automated retrieval of contextual relevant data using a personal computing device with speech recognition capabilities, capturing audio, parsing keywords, and mapping them to enterprise application records, such as CRM systems, to provide instant access to relevant information during a meeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If participants manually search for and retrieve data during an in-person meeting, then relevant information can be accessed, but the pace of interaction slows down and participant agility is limited
Solution Approach 1:
The system performs preliminary actions by continuously capturing audio and pre-processing speech recognition during the meeting. Keywords are identified and mapped to enterprise application records in advance, so that when a participant needs information, it is already prepared and can be instantly displayed without interrupting the meeting flow.
Solution Approach 2:
The meeting assistant system operates autonomously without requiring participant intervention. It automatically captures audio, performs speech recognition, identifies keywords, queries enterprise applications, and displays results - all without participants needing to manually search for information, thus maintaining the natural pace of interaction.
2Productivity
If participants focus on keeping pace with rapid idea exchange, then meeting momentum is maintained, but ability to retrieve real-time data is limited
Solution Approach 1:
The meeting assistant acts as an intermediary between participants and enterprise data systems. It handles all data retrieval operations in the background, allowing participants to focus entirely on idea exchange without being distracted by data search tasks. The intermediary translates speech into structured queries and returns results seamlessly.
Solution Approach 2:
The system replaces the manual mechanical process of data retrieval with automated speech recognition and database querying. Instead of participants physically typing searches or navigating systems, their spoken words are automatically converted into data queries, eliminating the time loss associated with manual data access.
3Loss of information
If automated speech recognition processes all audio without regard to speaker, then comprehensive data is captured, but processing complexity increases
Solution Approach 1:
The system extracts only the essential elements from the audio stream - specifically keywords and phrases relevant to enterprise data - rather than processing and analyzing every aspect of the speech. This extraction approach captures comprehensive information while avoiding the complexity of full speaker identification and contextual analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables rapid and efficient retrieval of contextual data, enhancing the pace and effectiveness of in-person meetings by providing participants with immediate access to relevant information through a user interface, thereby improving collaboration and data utilization.
Implementation Method 1
capturing speech audio in an in-person meeting through a transducer coupled to a personal computing device
Implementation Method 2
speech recognizing the captured speech audio by a processor of the computing device without regard to any speaker of the captured speech audio so as to produce a corpus of speech recognized text
Data Source
AI summary
Embodiments of the invention provide for the automated retrieval of contextual relevant data in an in-person meeting. In an embodiment of the invention, a method for the automated retrieval of contextual relevant data in an in-person meeting includes capturing speech audio in an in-person meeting through a transducer coupled to a personal computing device and speech recognizing the captured speech audio without regard to any speaker of the captured speech audio so as to produce a corpus of speech recognized text. The method also includes parsing the corpus of speech recognized text in order to identify a multiplicity of keywords and mapping the keywords to one or more records of an enterprise application. Finally, the method includes displaying a user interface to the enterprise application in the personal computing device and displaying in the user interface the one or more records.