Stylus Input Emotion Inference and Symbol Association
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Solution Overview
Problem
Current pen/stylus input technologies are limited in recognizing combinations of symbols and fail to leverage the speed and brevity of shorthand, missing the unconstrained nature of handwriting which includes letters, symbols, and evolving concepts.
Innovation Solution
An enhanced system that utilizes computer processing capabilities to interpret stylus inputs by identifying and associating symbols based on context, combinatorial structures, dimensionality, and emotional cues, allowing for flexible and intuitive user interactions, such as executing actions corresponding to combinations of symbols and retaining valuable information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If OCR technology is used to translate pen input like keyboard input by individual characters and words, then typing speed is improved, but the unconstrained nature of handwriting including letters, symbols, and evolving concepts is lost
Solution Approach 1:
The system performs multiple functions: it recognizes individual characters, identifies symbols, detects shorthand patterns, and interprets combinatorial structures. This multi-functional approach allows the system to handle both typed input (character-by-character) and handwritten input (symbols, shorthand, combinations) through a single unified platform, resolving the contradiction between typing speed and handwriting flexibility.
Solution Approach 2:
The system dynamically adapts its recognition approach based on the input characteristics. It can switch between character-level recognition (for typed-like input), symbol-level recognition (for shorthand), and combinatorial recognition (for symbol combinations). This dynamic adaptation allows the system to maintain typing speed for simple inputs while preserving handwriting flexibility for complex inputs.
2Productivity
If shorthand is used to speed up writing, then writing speed is improved, but current systems fail to recognize combinations of symbols
Solution Approach 1:
The system moves from one-dimensional character recognition to multi-dimensional recognition by analyzing spatial relationships between symbols, their positions, orientations, and combinations. This dimensional expansion allows the system to recognize shorthand symbols and their combinations accurately, maintaining both writing speed and recognition precision.
Solution Approach 2:
The system implements nested recognition levels: individual symbol recognition, combinatorial symbol recognition, and contextual meaning recognition. Each level builds upon the previous one, allowing the system to first identify individual shorthand symbols, then recognize their combinations, and finally interpret the overall meaning, thereby maintaining precision at all levels.
3Device complexity
If systems translate pen input by individual characters, then processing is simplified, but the speed and brevity of shorthand is not leveraged
Solution Approach 1:
The system segments the recognition process into distinct stages: symbol identification, combinatorial structure detection, shorthand pattern recognition, and contextual interpretation. This segmentation allows complex shorthand input to be processed efficiently by breaking it down into manageable components, reducing overall processing complexity while maintaining high input efficiency.
Solution Approach 2:
The system performs preliminary actions by pre-defining shorthand symbol libraries, combinatorial rules, and contextual associations. This preliminary preparation allows the system to quickly match user input against known patterns without performing complex analysis in real-time, thereby reducing processing complexity during actual use while maintaining high input efficiency.
Data Source
AI summary
An aspect provides a method including: identifying one or more symbols input to a surface of a first device; determining, using at least one processor, one or more modified input parameters associated with input of the one or more symbols; determining a modification to an association for the one or more symbols based on the one or more modified input parameters; and executing an action corresponding to a modified association for the one or more symbols. Other aspects are described and claimed.