Local Voice Command Identification Tool for IoT Delay Reduction
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Solution Overview
Problem
Existing voice control systems in IoT environments experience delays due to processing user voice commands in the cloud, leading to reduced reaction speed and efficiency in controlling multiple devices.
Innovation Solution
An electronic apparatus equipped with a microphone, transceiver, memory, and processor that performs voice recognition processing to acquire user intention information, retrieves status information of external devices, and identifies control commands using a control command identification tool, allowing for direct transmission to the device control server for faster device control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If voice recognition processing is performed through a cloud server, then voice recognition accuracy is improved, but processing time increases causing delay
Solution Approach 1:
The voice recognition system is segmented into two parts: complex voice recognition processing is performed by the cloud server to ensure accuracy, while simple control command identification is performed locally by the electronic apparatus to reduce delay. This segmentation allows each component to handle tasks appropriate to its capabilities.
Solution Approach 2:
The electronic apparatus performs preliminary filtering and preprocessing of voice recognition results before transmitting to the cloud server. By preparing data in advance and performing initial analysis locally, the system reduces the complexity of cloud processing and accelerates overall response time.
2Measurement precision
If control commands are identified by a cloud server, then command identification accuracy is improved, but system complexity increases
Solution Approach 1:
The control command identification function is extracted from the cloud server and implemented locally in the electronic apparatus. This extraction reduces system complexity by eliminating the need for complex cloud-based command identification infrastructure while maintaining adequate accuracy for control purposes.
Solution Approach 2:
The electronic apparatus performs self-service by independently identifying control commands using locally stored tools and algorithms. This self-service capability reduces dependence on external cloud services and simplifies the overall system architecture.
3Measurement precision
If status information of multiple external devices is retrieved and processed, then device control accuracy is improved, but processing time increases
Solution Approach 1:
The electronic apparatus retrieves only the necessary status information of external devices rather than complete device states. By selecting only relevant parameters needed for control decisions, the system maintains accurate control while minimizing data retrieval and processing time.
4Speed
If voice recognition processing is performed locally in the electronic apparatus, then reaction speed is improved, but recognition accuracy may decrease
Solution Approach 1:
Voice recognition processing is segmented between local and cloud components. The electronic apparatus performs initial voice recognition locally to achieve fast reaction speed, then transmits results to the cloud server for verification and refinement to maintain accuracy.
Data Source
AI summary
An electronic apparatus is provided. The electronic apparatus includes a microphone, a transceiver, a memory configured to store a control command identification tool based on a control command identified by a voice recognition server that performs voice recognition processing on a user voice received from the electronic apparatus, and at least one processor configured to, based on the user voice being received through the microphone, acquire user intention information by performing the voice recognition processing on the received user voice, receive status information of external devices related to the acquired user intention information from a device control server, identify a control command for controlling a device to be controlled among the plurality of external devices by applying the acquired user intention information and the received status information of the external devices to the control command identification tool, and transmit the identified control command to the device control server.