On-Device Text Recognition for Email Draft Import
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Solution Overview
Problem
Current methods for importing text from external sources into email drafts on user devices are cumbersome and time-consuming, often requiring scanning, character recognition, and external equipment, or result in non-editable image formats that display inconsistently across devices.
Innovation Solution
A user device system that includes a hardware-based processor and memory, utilizing a machine learning model for on-device text recognition, allowing users to capture images or select files for automatic text importation into email drafts, with options to edit and manipulate the recognized text, and providing accuracy indicators.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a user scans a hard-copy document, performs character recognition, and copies text into an email, then the text can be imported into the email draft, but the process becomes complex and time-consuming
Solution Approach 1:
The patent combines multiple functions (camera capture, text recognition, and email composition) into a single integrated workflow. The camera interface is directly launched from the email draft screen, and text recognition is automatically performed on captured images, merging what were previously separate processes into one seamless operation.
Solution Approach 2:
The system provides multiple input methods (camera capture and file selection) for text importation, making the email client universally capable of handling different text sources. The same interface and processing pipeline handle both photographed documents and uploaded files, providing multi-functional text import capability.
2Productivity
If a user takes a picture of text and uses it in the draft email, then the process is quick and simple, but the text becomes non-editable and displays differently on different devices
Solution Approach 1:
The patent replaces the mechanical approach of inserting image files with an automated optical character recognition system. Instead of manually inserting pictures and hoping for text extraction, the system automatically recognizes text from captured images and inserts it as editable text content, substituting a sophisticated automated process for simple file insertion.
Solution Approach 2:
The system performs text recognition automatically without requiring user intervention. When a user captures an image of text, the system self-servicefully recognizes the text, extracts it, and inserts it into the email draft as editable content, eliminating the need for manual text entry or formatting adjustments.
3Measurement precision
If external scanning equipment is used to convert documents to text, then text recognition accuracy can be improved, but device complexity and portability are reduced
Solution Approach 1:
The patent extracts the text recognition functionality from external scanning equipment and integrates it directly into the mobile device. The character recognition capability is built into the email client, allowing the device to independently perform text recognition on captured images without requiring external scanners or specialized hardware.
Solution Approach 2:
The system uses the device's camera as an intermediary between the physical document and the digital text. Instead of requiring direct connection to external scanning equipment, the camera captures an image of the document, which then serves as input for the integrated text recognition system, providing a simple intermediate step that eliminates complex hardware requirements.
4Reliability
If multiple steps are required for document conversion and text import, then text import accuracy can be maintained, but user-friendly operation is reduced
Solution Approach 1:
The system performs text recognition in advance during the capture process itself. When the user takes a picture of a document, the text recognition is automatically performed before the user needs to compose the email, so that when the user finishes reviewing the captured image, the text is already extracted and ready to be inserted into the email draft.
Data Source
AI summary
Examples described herein include systems and methods for importing text into a draft email on a user device. In response to a user selecting the first selectable element, the user device can launch a camera interface on the display. The user can capture an image, such as a page of a book or newspaper, and then scale the captured image to the relevant desired portion. The example method can further include recognizing text within the scaled portion of the image and automatically importing the recognized text into the draft email. The user device can utilize a machine learning model to perform text recognition at the device and then insert the recognized text into the draft email automatically. The user device can also display an indication of the accuracy of the imported recognized text within the draft email.