Graphical Keyboard Automatic Language Identification and Decoder Switching
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Solution Overview
Problem
Graphical keyboards often fail to accurately decode user input when the user types in a language different from the default language configured, leading to incorrect behavior and a frustrating user experience, as they lack the capability to automatically identify and switch to the intended language.
Innovation Solution
A graphical keyboard that employs a language identification module to determine the target language of user input and automatically reconfigures itself by enabling the appropriate decoder, either by switching between existing decoders or downloading and installing new ones as needed, to ensure accurate text decoding across multiple languages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a graphical keyboard uses a default language decoder configured for a specific language, then it can accurately decode inputs in that language, but it fails to accurately decode inputs when the user types in a different language
Solution Approach 1:
The keyboard system dynamically switches between different language decoders based on detected input patterns. The language identification module continuously monitors user input and automatically transitions from a static default decoder to the appropriate decoder for the detected language, making the system adaptive rather than fixed
Solution Approach 2:
The system performs self-diagnosis through the language identification module that analyzes input patterns and automatically determines when a language mismatch occurs. It then self-corrects by switching decoders without requiring user intervention, enabling the system to serve itself in maintaining accurate decoding
2Adaptability or versatility
If the graphical keyboard automatically identifies and switches decoders for multiple languages, then it improves adaptability and user experience, but it increases device complexity and power consumption
Solution Approach 1:
The language identification module serves as an intermediary between the user input and the decoder selection mechanism. This mediator analyzes input patterns and translates them into appropriate decoder selections, simplifying the overall system architecture by centralizing the decision-making logic in a dedicated component rather than distributing complexity throughout the decoding system
Solution Approach 2:
The keyboard system achieves multi-functionality by incorporating a single language identification module that can recognize multiple languages and route to appropriate decoders. This universal approach allows one component to handle diverse language scenarios, reducing the need for separate specialized systems for each language
3Productivity
If the graphical keyboard automatically switches decoders based on language identification, then it reduces the number of user inputs required for text entry, but it increases the processing time and power consumption
Solution Approach 1:
The language identification module performs partial analysis of user input to detect language patterns, rather than analyzing every single character in depth. This selective approach provides sufficient information for accurate language detection while minimizing unnecessary processing and energy consumption
Data Source
AI summary
A keyboard is described that determines, using a first decoder and based on a selection of keys of a graphical keyboard, text. Responsive to determining that a characteristic of the text satisfies a threshold, a model of the keyboard identifies the target language of the text, and determines whether the target language is different than a language associated with the first decoder. If the target language of the text is not different than the language associated with the first decoder, the keyboard outputs, for display, an indication of first candidate words determined by the first decoder from the text. If the target language of the text is different: the keyboard enables a second decoder, where a language associated with the second decoder matches the target language of the text, and outputs, for display, an indication of second candidate words determined by the second decoder from the text.