Voice Document Editing With Semantic Annotations for Mobile Review
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Solution Overview
Problem
Existing document editing systems require significant user interaction and resource consumption, limiting editing capabilities to desktop environments and delaying collaborative document review due to the need for graphical user interfaces, especially on mobile devices.
Innovation Solution
An automated assistant that allows users to perform document-related tasks through verbal interactions, utilizing semantic annotations and machine learning models to edit, comment, and share documents across various devices without direct graphical interface access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If document editing is performed through traditional graphical user interfaces on desktop devices, then editing functionality is comprehensive, but user dexterity is fully consumed and resource consumption is high
Solution Approach 1:
The patent replaces the mechanical interaction system (keyboard, mouse, touch screen) with a voice-based natural language processing system. Users can edit documents by speaking commands instead of manually typing or navigating through graphical interfaces, thereby reducing physical dexterity consumption and device resource usage while maintaining comprehensive editing functionality
Solution Approach 2:
The patent introduces an automated assistant as an intermediary between the user and the document editing system. The assistant processes voice commands, interprets user intent, and executes editing operations, eliminating the need for users to directly interact with resource-intensive graphical interfaces while still accessing full editing capabilities
2Productivity
If document review is restricted to desktop-style graphical interfaces, then editing functionality is complete, but review time is delayed and collaboration efficiency is reduced
Solution Approach 1:
The patent replaces the graphical interface-based review process with voice-based interaction, allowing reviewers to quickly assess documents by speaking commands without navigating through visual interfaces. This significantly reduces review time while maintaining the ability to access and evaluate all document content
Solution Approach 2:
The system prepares document content in advance for voice-based review, organizing and structuring information so that reviewers can efficiently query and assess documents through natural language commands without the time loss associated with loading and navigating graphical interfaces
3Adaptability or versatility
If multiple users edit documents simultaneously through cloud applications, then collaboration is enabled, but resource consumption increases and access limitations persist
Solution Approach 1:
The patent introduces voice-based automated assistants as intermediaries for each user in the collaboration process. These assistants handle document access, editing operations, and synchronization tasks, reducing the computational burden on individual devices while enabling seamless multi-user collaboration through natural language commands
Solution Approach 2:
The system creates and manages copies of document states for different users, allowing simultaneous access and editing through voice commands. Each user's automated assistant works with local copies or cached versions of the document, reducing the need for continuous high-bandwidth synchronization while maintaining collaboration capabilities
Data Source
AI summary
Implementations set forth herein relate to an automated assistant that allows a user to create, edit, and/or share documents without directly interfacing with a document editing application. The user can provide an input to the automated assistant in order to cause the automated assistant to interface with the document editing application and create a document. In order to identify a particular action to perform with respect to a document, and/or identify a particular subsection within the document to direct the action, the automated assistant can rely on semantic annotations. As a user continues to interact with the automated assistant to edit a document, the semantic annotations can be updated according to how the document is changing and/or how the user refers to the document. This can allow the automated assistant to more readily fulfill document-related requests that may lack express details.


