Language Preference Selection Using Non-Language Interface Elements
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Solution Overview
Problem
Current computer interfaces face difficulties in allowing users to select a specific language, particularly dialects or variants, due to large lists of languages and the lack of effective ordering, leading to an onerous selection process.
Innovation Solution
A computer-implemented method that uses non-language elements, such as ideograms, to prompt users for initial responses to determine a language, followed by language elements in the determined language to elicit further responses for sub-language selection, allowing for precise dialect or regional variant identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a list of all supported languages is provided to users, then language selection completeness is improved, but user interface complexity and selection difficulty increase
Solution Approach 1:
The patent segments the language selection process into multiple stages: first presenting a manageable subset of languages, then offering to add more languages if needed. This divides the overwhelming complete list into manageable portions, reducing initial interface complexity while maintaining language selection completeness.
Solution Approach 2:
The system performs preliminary action by detecting the user's language preference automatically before presenting the language list. This preliminary detection allows the interface to be simplified by showing only relevant languages or a reduced set, rather than presenting all supported languages from the start.
2Adaptability or versatility
If a large number of language options are presented, then language coverage is improved, but selection time and user burden increase
Solution Approach 1:
The patent implements feedback mechanisms where the system observes user interactions with the language interface (such as which languages are selected or ignored) and uses this feedback to refine future language presentations. This feedback loop reduces selection time by learning from user behavior while maintaining comprehensive language coverage.
Solution Approach 2:
The system dynamically changes parameters such as the number of languages displayed, the ordering of languages, and the presentation format based on detected user preferences and behavior. This parameter adjustment reduces selection time by adapting the interface to individual users while preserving full language coverage availability.
3Reliability
If languages are presented in native scripts without ordering, then language authenticity is improved, but selection ease deteriorates
Solution Approach 1:
The system performs preliminary ordering of languages based on detected user preferences, geographic location, or usage patterns before presenting them to the user. This preliminary action maintains language authenticity through native scripts while improving selection ease through intelligent ordering, placing the user's likely preferred languages at the top of the list.
Data Source
AI summary
Described is a technique for establishing an interaction language for a user interface without having to communicate with the user in a default language, which the user may or may not understand. The technique may prompt the user for multiples responses in order to determine a specific language. The responses may include speech input or selecting particular regions on a map. In some implementations, the language may be precise to a particular dialect or variant preferred or spoken by the user. Accordingly, this approach provides an accurate and efficient method of providing a high degree of specificity for language selection without overwhelming the user with an unmanageable list of languages.