Audio-to-Work Record Linking for Faster Collaboration Search

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Solution Overview

Problem

Operating web-based collaboration environments is challenging due to inefficient and error-prone manual creation and management of work unit records, requiring human-machine interactions that decrease workflow efficiency and necessitate time-consuming searches through lengthy recordings for relevant information.

Innovation Solution

A system utilizing a trained machine learning model to generate correspondences between portions of recorded audio/video content and work unit records, allowing users to quickly access relevant content through intuitive user interfaces.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If users manually create and manage work unit records from recorded content, then record accuracy and completeness can be maintained, but workflow efficiency decreases and time consumption increases

Engineering Contradiction:

Improverecord accuracyVSAvoidworkflow efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The system enables automatic generation of work unit records by having the recorded content itself serve as the source material. The system automatically transcribes audio recordings, extracts action items and tasks, and creates structured records without requiring manual user intervention, thus maintaining reliability while improving productivity

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of users reading recordings and manually creating records with an automated system using speech-to-text conversion, natural language processing, and machine learning algorithms to generate work unit records automatically

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Loss of information

If users manually search through lengthy recordings to find relevant information, then complete context can be reviewed, but time consumption increases and workflow efficiency decreases

Engineering Contradiction:

Improvecontext completenessVSAvoidsearch time

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system extracts specific relevant portions from lengthy recordings by automatically identifying action items, tasks, and key decisions mentioned in the recording. It pulls out only the essential information needed for work unit records, eliminating the need for users to search through entire recordings while maintaining context completeness

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary analysis of recorded content by automatically transcribing and processing the audio before users need to access it. Action items and relevant information are pre-identified and organized into structured records, so users can immediately access relevant information without searching

Inventive Principle:

Principle #10Preliminary action

3Productivity

If automated systems are used to generate work unit records from recorded content, then workflow efficiency improves and time consumption decreases, but accuracy and completeness may deteriorate

Engineering Contradiction:

Improveworkflow efficiencyVSAvoidrecord accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system incorporates feedback mechanisms where generated work unit records can be reviewed, edited, and corrected by users. The system learns from user corrections and refinements, continuously improving the accuracy and completeness of automatically generated records while maintaining high workflow efficiency

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent introduces an intermediary layer between the recorded content and the final work unit records. This intermediary system uses natural language processing and machine learning to interpret and structure the content, providing a bridge that maintains accuracy while enabling automated generation

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS12579515B2Systems and methods to train and/or use a machine learning model to generate correspondences between portions of recorded audio content and work unit records of a collaboration environment

Publication Date: 2026.03.17 ASANA INC

AI summary

Systems and methods to train a machine learning model to generate correspondences between portions of recorded content and records of a collaboration environment and/or generate correspondences between portions of recorded content and records of a collaboration environment using a trained machine learning model. Exemplary implementations may perform one or more of: manage environment state information maintaining a collaboration environment; obtain correspondence information conveying user-provided correspondences between temporal content of recorded audio content and records; compile the correspondence information and information from records into input/output pairs; train a machine learning model based on the input/output pairs; store the trained machine learning model; provide other information from records and recorded content as input into the trained machine learning model; obtain output from the trained machine learning model including automatically generated correspondence information; and/or other operations.