Electronic Device Control Through Situation-Based Utterances
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Solution Overview
Problem
Existing devices require explicit commands for multiple devices, necessitating clear identification of the device to execute each command, limiting flexibility in controlling multiple devices simultaneously.
Innovation Solution
An electronic device that classifies user utterances based on situation factors to indirectly discern intent and generate action scenarios for multiple external devices, using a communication module, memory, and processor to interpret user inputs and control devices accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If explicit commands are used for each device, then device control accuracy is improved, but operation complexity increases and flexibility decreases
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates colloquial user utterances into structured device control commands. The system uses an intent recognition module and entity extraction module as intermediaries between the user's casual speech and the precise device control signals, allowing users to speak naturally while maintaining accurate device control.
Solution Approach 2:
The system employs self-service through automatic device identification and command routing. When a user provides an indirect utterance, the system automatically identifies the target device, extracts the control intent, and executes the appropriate command without requiring the user to manually specify device identifiers or follow rigid command formats.
2Measurement precision
If multiple devices are controlled simultaneously with explicit commands, then control precision is improved, but the number of commands required increases
Solution Approach 1:
The patent merges multiple device control operations into a single natural language utterance. The system processes a unified command that can simultaneously target multiple devices, extracting and distributing control intents to relevant devices in parallel, thereby reducing the total number of separate commands users must issue.
Solution Approach 2:
The system performs preliminary action by pre-configuring device relationships and control patterns. During setup, the system learns which devices are related and how they should be controlled together, enabling it to automatically group and control multiple devices based on pre-established associations rather than requiring users to specify each device individually each time.
3Measurement precision
If device identification is required for each command, then command accuracy is improved, but user burden increases
Solution Approach 1:
The system implements self-service through automatic device identification. The entity extraction module and device matching module automatically identify which device or devices the user intends to control based on contextual clues in the utterance, eliminating the need for users to manually specify device identifiers while maintaining accurate command routing.
Solution Approach 2:
The patent applies parameter changes by dynamically adjusting the level of device specification required based on the clarity of the user's utterance. When the intent is clear from context, the system accepts less specific input; when ambiguity exists, it requests additional clarification, thereby adapting the complexity requirements to the specific interaction context.
Data Source
AI summary
An electronic device is disclosed that, in response to at least one of an utterance intent and a control target device not being identified from utterance data, classifies a situation factor based on the utterance data, determines one or more external devices that match the classified situation factor, and generates and presents to the user terminal one or more action scenarios for one or more external devices determined for the classified situation factor.