Speech Recognition Device Control via Dynamic Process Transition
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Solution Overview
Problem
Existing speech recognition technologies face challenges in accurately interpreting and responding to human language instructions, leading to inadequate device control.
Innovation Solution
A device control system that includes input information identification, process-item data storage, transition-definition data storage, and an update mechanism to access and update process items and transition definitions based on input information, allowing for accurate selection and execution of corresponding device control actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If speech recognition technology is used to control devices, then device control functionality is provided, but accurate recognition and interpretation of human language instructions cannot be achieved
Solution Approach 1:
The speech recognition process is divided into multiple stages: speech signal input, language analysis for candidate word identification, and structured database matching. This segmentation allows each stage to be optimized independently, improving overall recognition accuracy while maintaining reliable device control functionality.
Solution Approach 2:
A structured database containing process items and transition definitions is introduced as an intermediary between speech recognition and device control. This database acts as a mediator that translates recognized speech into actionable control commands, bridging the gap between imperfect speech recognition and reliable device control.
2Measurement precision
If a structured database with process items and transition definitions is implemented, then speech input processing accuracy is improved, but system complexity increases
Solution Approach 1:
The structured database serves multiple functions simultaneously: it stores process items, defines transition rules, and provides the basis for speech-to-action mapping. This multi-functionality reduces the need for separate components, managing system complexity while maintaining high processing accuracy.
Solution Approach 2:
The system dynamically selects and transitions between process items based on recognized speech input and predefined transition definitions. This dynamic behavior allows the system to adapt to different speech commands without requiring a static, overly complex structure for each possible command scenario.
3Reliability
If transition definition data with conditions is used to select process items, then response accuracy to speech instructions is improved, but data processing complexity increases
Solution Approach 1:
Transition definitions and their associated conditions are pre-configured in the structured database before runtime operation. This preliminary preparation allows the system to quickly match recognized speech against predefined conditions without performing complex real-time analysis, improving response accuracy while managing processing complexity.
Solution Approach 2:
The system uses template-based process items and transition definitions that can be replicated and reused for different speech commands. Instead of creating unique processing logic for each command, standardized templates are copied and adapted, reducing data processing complexity while maintaining high response accuracy.
Data Source
AI summary
A language analyzer performs speech recognition on a speech input by a speech input unit, specifies a possible word which is represented by the speech, and the score thereof, and supplies word data representing them to an agent processing unit. The agent processing unit stores process item data which defines a data acquisition process to acquire word data or the like, a discrimination process, and an input/output process, and wires or data defining transition from one process to another and giving a weighting factor to the transition, and executes a flow represented generally by the process item data and the wires to thereby control devices belonging to an input/output target device group. To which process in the flow the transition takes place is determined by the weighting factor of each wire, which is determined by the connection relationship between a point where the process has proceeded and the wire, and the score of word data. The wire and the process item data can be downloaded from an external server.