Predictive Text Input System for Mobile Devices
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Solution Overview
Problem
Conventional human-to-mobile interfaces require excessive physical keying or tapping events to create data strings, leading to inefficiency and increased user interaction, which can result in fatigue and errors.
Innovation Solution
A method and system that reduces the number of physical interactions by using character recognition and predictive text input, where data strings are stored with priority indicators based on derivatives such as frequency of use, context, and grammar, allowing for dynamic selection and suggestion of subsequent characters, thereby reducing the need for repetitive key presses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional physical keyboard input methods are used, then data input can be achieved, but the number of physical keying actions and tapping actions required is excessive
Solution Approach 1:
The system pre-calculates and stores priority indicators for multiple potential subsequent data strings based on derivatives of the current data string before the user actually needs to input the next character. This preliminary preparation allows the prediction interface to be instantly available, reducing waiting time and making the input process more efficient.
Solution Approach 2:
A prediction interface acts as an intermediary between the user and the data string creation process. Instead of directly inputting each character through physical keying, the user interacts with the prediction interface which mediates by suggesting and facilitating selection of predicted data strings, thereby reducing the number of physical actions required.
2Productivity
If conventional physical keyboard input methods are used, then data strings can be created, but the number of physical keying actions and tapping actions exceeds the number of characters in the data string
Solution Approach 1:
The prediction interface serves multiple functions: it predicts subsequent data strings, ranks them by priority, presents them to the user, and facilitates selection. This multi-functionality consolidates what would otherwise require separate processes into a single integrated interface, improving productivity without proportionally increasing device complexity.
Solution Approach 2:
The system automatically performs the work of generating predictions, calculating priorities, and preparing the prediction interface without requiring user intervention. The user simply needs to trigger the prediction function and select from presented options, allowing the system to serve itself in the complex tasks of prediction and ranking.
3Ease of operation
If predictive text input with priority indicators is implemented, then the number of physical keying actions is reduced, but the system complexity increases
Solution Approach 1:
The prediction system is segmented into distinct functional components: a prediction engine that generates subsequent data strings, a priority calculation module that computes priority indicators based on derivatives, and a presentation interface that displays options to the user. This segmentation allows each component to be optimized independently and managed separately, making the overall complex system more maintainable and understandable.
Data Source
AI summary
A method of character recognition for a personal computing device comprising a user interface capable of receiving inputs that are to be recognized through data input means which are receptive to keyed, tapped or a stylus input, said device being adapted to facilitate a reduction in the number of physical keying actions, tapping actions or gestures required to create a data string to less than the number of characters within said data string: storing a set of data strings each with a priority indicator associated therewith, wherein the indicator is a measure of a plurality of derivatives associated with the data string; recognizing an event; looking up the most likely subsequent data string to follow the event from the set of data strings based on one or more of the plurality of derivatives; ordering the data strings for display based on the priority indicator of that data string.