Segmented Sign Language Keyboard for Accurate Meaning Input
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Solution Overview
Problem
Existing sign language input and search systems face challenges in accurately reflecting the meaning content of sign language due to the complexity of finger and non-finger actions, which are difficult to analyze and require multiple operations, and are not easily accessible for hearing-impaired individuals, especially those with limited dexterity or aged users.
Innovation Solution
A sign language keyboard and searching apparatus with divided upper body, finger, and wrist state input areas that allow for easy and convenient input and search of sign language information by discriminating finger shapes, upper body positions, and wrist actions, using a general-purpose keyboard or touch panel screen, enabling efficient conversion of sign language into text.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If morphological analysis and conversion into fragmented sign language picture image data are performed, then the information can be recognized by hearing-impaired persons, but the meaning content of the sentence data is hardly reflected correctly and multiple operations are required
Solution Approach 1:
The keyboard is segmented into distinct functional areas: finger input areas (for finger shapes), upper body input areas (for non-finger actions), and wrist state input areas (for wrist orientations). This segmentation allows each area to capture specific components of sign language independently, simplifying the overall input process while maintaining accurate meaning content reflection.
Solution Approach 2:
The system performs preliminary classification of sign language components into finger shapes, upper body positions, and wrist states before final meaning determination. By pre-organizing the input data structure and capturing all necessary components simultaneously through the divided keyboard areas, the system eliminates the need for multiple sequential operations and morphological analysis steps.
2Measurement precision
If image analysis of animation images is performed to convert into words and sentences, then sign language can be recognized, but it is difficult to perform image analysis due to delicate differences in finger and non-finger actions depending on character or personality
Solution Approach 1:
Instead of analyzing complete animation images, the system segments sign language input into discrete, standardized components: finger shapes, upper body positions, and wrist states. Each component is captured by dedicated keyboard areas with predefined options, eliminating the complexity of analyzing delicate variations in continuous video data while maintaining recognition accuracy.
Solution Approach 2:
The system uses a standardized keyboard interface that copies the essential structure of sign language into a simplified digital format. Rather than attempting to analyze and interpret natural sign language variations from video, the system creates a standardized representation through structured key inputs, making detection and measurement straightforward.
3Adaptability or versatility
If large motions of both hands and upper body are required for sign language expression, then complete sign language can be expressed, but it is difficult for hearing-impaired persons who are impaired in fingers and/or hands and/or who are aged
Solution Approach 1:
The keyboard divides sign language input into separate functional areas: finger input areas for hand shapes, upper body input areas for body positioning, and wrist state input areas for wrist orientation. This segmentation allows users to input each component independently through simplified key presses rather than requiring large physical motions, maintaining complete sign language expression capability while improving ease of operation for users with limited dexterity.
4Loss of information
If cards or the like previously divided into finger action and non-finger action are prepared to learn meaning contents, then meaning content can be learned, but the input system is not handled more easily or simply
Solution Approach 1:
The keyboard merges the previously separate finger action cards and non-finger action cards into a single integrated interface. All sign language components (finger shapes, upper body positions, wrist states) are available simultaneously on one keyboard, allowing users to input complete meaning content through a unified, simple operation rather than requiring multiple separate card sets or complex multi-step processes.
Data Source
AI summary
Expression by sign language can be inputted more easily and reliably, and search can be performed therefor as well. A general-purpose keyboard is divided into finger input areas in which shapes of fingers are allotted to respective key tops and upper body input areas in which divided portions of an upper body of a sign language talker are allotted to key tops so that information, which is meant by the sign language, can be inputted by the aid of the keyboard in cooperation of key inputs of the respective areas.