Canned Answers Using Predictive Text for Small Touch Keyboards
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Solution Overview
Problem
The small form factor of portable electronic devices presents challenges for efficient message-based communication due to reduced-size keyboards, which are sub-optimal for typing, exacerbated by advancements in electronics packaging that further reduce keyboard space.
Innovation Solution
Implementing predictive text input methods on touch-sensitive displays that suggest characters or phrases based on the content of incoming messages, allowing users to select from displayed suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of moving object
If the form factor of portable electronic devices is reduced, then the device becomes more compact and portable, but the keyboard size is reduced making it sub-optimal for typing
Solution Approach 1:
The patent replaces the mechanical keyboard input system with a predictive text generation system. Instead of relying on physical keys, the system uses machine learning models to predict and generate text responses automatically, substituting the mechanical typing process with an intelligent text generation approach that works on touch displays.
Solution Approach 2:
The system performs self-service by automatically generating and providing text responses based on the message context. The predictive text model analyzes the conversation history and incoming message to autonomously generate appropriate responses, reducing the need for manual user input and making the device self-sufficient in the text generation task.
2Productivity
If predictive text input is implemented to reduce manual input, then message response efficiency is improved, but device complexity increases
Solution Approach 1:
The predictive text system is integrated into the existing messaging application framework, serving multiple functions: it provides text completion, generates responses, and adapts to user preferences. By making the system multi-functional and integrating it with existing components, the patent reduces the overall complexity burden despite adding predictive capabilities.
Solution Approach 2:
The system dynamically adjusts its behavior based on contextual parameters such as conversation history, message content, and user interaction patterns. By changing parameters like prediction confidence thresholds and model selection based on the specific messaging context, the system optimizes performance while managing complexity through adaptive rather than fixed architecture.
Data Source
AI summary
At an electronic device with a touch-sensitive display, display a message transcript, where the message transcript includes at least one message from at least a first user. Determine, based at least in-part on the at least one message, a plurality of suggested one or more characters. Display, on the touch-sensitive display, the plurality of suggested one or more characters. Detect an input on the touch-sensitive display. Determine whether the input represents user selection of one of the plurality of suggested one or more characters. Display the selected one of the plurality of suggested one or more characters in the message transcript. Send the selected one or more characters to the first user.