AI Document Review Feedback Annotation System
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Solution Overview
Problem
Current methods for document review meetings face challenges in accurately capturing and consolidating feedback and suggested edits from participants, as they often rely on manual note-taking and handwritten comments, which can lead to inconsistencies and inefficiencies in incorporating feedback into the original document.
Innovation Solution
An apparatus comprising processors and memories that automatically identify and generate annotations for content suggestions from various sources, including physical and electronic documents, media content, and third-party systems, allowing for efficient integration of feedback into the original document content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual note-taking and handwritten comments are used to capture feedback during document review meetings, then participants can provide suggestions, but the accuracy and consistency of capturing all feedback deteriorates
Solution Approach 1:
The patent replaces manual note-taking and handwritten comments with an automated speech-to-text system that transcribes spoken feedback during meetings. The system uses speech recognition to convert verbal suggestions into structured text annotations, eliminating the need for manual transcription and significantly improving the accuracy and consistency of feedback capture while maintaining ease of participation.
2Quantity of substance
If manual consolidation of comments and suggested edits is performed, then feedback can be collected, but the efficiency and time required to incorporate feedback deteriorates
Solution Approach 1:
The system enables self-service by automatically transcribing, structuring, and organizing feedback without requiring manual consolidation efforts. The speech-to-text conversion and automated annotation generation allow the system to process and incorporate feedback independently, significantly improving efficiency while handling large volumes of suggestions.
Solution Approach 2:
The patent introduces an intermediary automated processing layer between feedback collection and document update. This intermediary system uses speech recognition and natural language processing to convert verbal feedback into structured annotations that can be directly applied to the document, streamlining the incorporation process and reducing manual effort.
3Productivity
If automated speech-to-text conversion and annotation generation are implemented, then the efficiency and accuracy of capturing feedback improves, but the device complexity increases
Solution Approach 1:
The system achieves multi-functionality by combining speech-to-text conversion, feedback transcription, annotation generation, and document update capabilities into a single integrated platform. This universal system handles multiple tasks that would otherwise require separate tools, improving efficiency while managing complexity through consolidation of functions.
Data Source
AI summary
Artificial intelligence is introduced into document review to identify content suggestions from input to generate suggested annotations for the reviewed document. An approach is provided for receiving an electronic document that contains original content from an original electronic document for review and electronic mark-ups provided by a first user. One or more electronic mark-ups that represent content suggestions proposed by the first user are identified from the electronic document. For each electronic mark-up of the one or more electronic mark-ups identified a document portion of the original content that corresponds to the electronic mark-up is identified, and an annotation is generated for the electronic mark-up comprising the electronic mark-up and a first user ID for the first user and associating the annotation to the document portion identified. The original content with one or more annotations generated from the one or more electronic mark-ups is displayed, in electronic form, within a display window.