Touch Input Syntax Analysis and Auto-Formatting
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Solution Overview
Problem
Current input methods in devices like tablets and smartphones often result in user errors due to incorrect space insertion and formatting issues, especially when entering specific data types like email addresses or phone numbers, and existing auto-correction systems fail to accurately recognize and format these inputs correctly.
Innovation Solution
A method that uses a processor to identify the syntax and modify user input based on detected characteristics, such as grammatical structure and spacing patterns, to ensure correct formatting and insertion into the intended data field, even when using non-standard input methods like handwriting or touch input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional soft keyboard or handwriting input methods are used, then users can input text conveniently, but user errors occur due to incorrect space insertion and formatting issues
Solution Approach 1:
The system performs preliminary analysis of the input context (data field type, expected format) before the user completes their input. By pre-identifying the target field's requirements and preparing appropriate formatting rules, the system can automatically correct spacing and formatting issues as the user types, preventing errors before they occur rather than correcting them afterward.
Solution Approach 2:
The system continuously monitors user input in real-time, compares it against the expected format of the target data field, and provides immediate feedback by automatically inserting spaces or correcting formatting. This closed-loop feedback mechanism allows the system to adapt to user input patterns while maintaining formatting accuracy, resolving the contradiction between ease of input and input reliability.
2Extent of automation
If existing auto-correction systems are used, then some formatting issues are addressed, but they fail to accurately recognize and format specific data types like email addresses or phone numbers
Solution Approach 1:
The system applies different formatting rules and recognition criteria tailored to specific data field types. Instead of using a generic auto-correction approach, it customizes the correction logic for each field type (email addresses get @ symbol preservation, phone numbers get space insertion in specific patterns, URLs get protocol handling). This localized approach to quality control enables accurate recognition and formatting of specific data types while maintaining high automation.
Solution Approach 2:
The system pre-loads and identifies the expected format requirements for different data field types before user input occurs. By having the target field's formatting specifications ready in advance, the auto-correction system can accurately anticipate what format is needed and apply the correct transformations, improving data type recognition accuracy while maintaining automation.
3Reliability
If manual formatting correction is implemented, then input accuracy improves, but user time and operational complexity increase
Solution Approach 1:
The system performs formatting corrections automatically without requiring user intervention. The user simply inputs their text naturally, and the system self-corrects spacing, formatting, and data type-specific issues autonomously. This eliminates the time users would otherwise spend manually adjusting their input while maintaining high formatting accuracy, as the correction process occurs in the background without adding operational steps.
Solution Approach 2:
The system prepares formatting corrections in advance and applies them automatically as the user types, rather than requiring the user to review and correct input afterward. By performing the correction action preliminarily and automatically, the system achieves high input formatting accuracy without consuming user time, as the corrections happen transparently during the natural input process.
Data Source
AI summary
One embodiment provides a method, including: receiving, on a touch input device, user input; indentifying, using a processor, syntax in the user input; modifying, based on the identified syntax, the user input; and inserting, using a processor, the modified user input into a data field. Other aspects are described and claimed.