Speech Recognition Device Automatic Model Selection
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Solution Overview
Problem
The task of preselecting an appropriate speech recognition model is burdensome for users, particularly in industrial machinery applications where accuracy is crucial.
Innovation Solution
A speech recognition device that includes an acceptance unit, parameter storage unit, temporary setting parameter selection unit, recognition unit, and parameter selection unit, which narrows down parameters based on input information to automatically select the most suitable speech recognition model for accurate speech recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a user manually preselects an appropriate speech recognition model, then speech recognition accuracy can be improved, but user workload and operation complexity increase
Solution Approach 1:
The system performs self-selection of speech recognition models by automatically analyzing narrowed information from speech inputs and selecting appropriate models without user intervention. The model selection unit autonomously determines which model to use based on the analysis results, eliminating the need for manual user selection while maintaining high accuracy.
Solution Approach 2:
The system uses feedback from speech recognition results to refine future model selections. By analyzing the narrowed information obtained from speech inputs and comparing it with stored reference information, the system continuously improves its model selection accuracy, creating a feedback loop that enhances both accuracy and automation.
2Measurement precision
If multiple speech recognition models are provided to increase accuracy, then speech recognition accuracy improves, but device complexity and difficulty of configuration increase
Solution Approach 1:
The system performs preliminary analysis of speech inputs to determine the appropriate model before actual recognition occurs. The analysis unit pre-processes the speech information to extract narrowed information, which then guides the model selection unit in choosing the most suitable model in advance, simplifying the overall system complexity.
Solution Approach 2:
The system segments the model selection process into distinct functional units: an analysis unit that processes speech information, a selection unit that chooses models based on analysis, and a storage unit that manages reference information. This segmentation allows each component to handle specific tasks independently, reducing overall system complexity while maintaining multiple model capabilities.
Data Source
AI summary
This speech recognition device is provided with: an acceptance unit that accepts input of speech information; a parameter storage unit that stores a plurality of parameters for setting a speech recognition model; a temporary setting parameter selection unit that selects, on the basis of narrowing information, a temporary setting parameter to be temporarily set, from the plurality of parameters; a recognition unit that recognizes speech information on the basis of the selected temporary setting parameter; and a parameter selection unit that selects, on the basis of information indicating a recognition result of the recognized speech information, one of the temporary setting parameters.