Voice Recognition Apparatus Server-Based Algorithm Update
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Solution Overview
Problem
Existing voice recognition systems for home appliances face limitations in recognizing natural languages due to constraints in system resources, making it difficult to implement efficient voice command processing across various languages without requiring significant computational power within individual apparatus modules.
Innovation Solution
A voice recognition apparatus and system that utilize a server-based approach, where a microphone captures voice commands and transmits them to a server system for processing, allowing for updates of the voice recognition algorithm to optimize performance based on user characteristics and regional languages, enabling efficient natural language recognition and control of home appliances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If voice recognition processing is performed locally in individual apparatus modules, then response speed is improved, but system resource constraints prevent efficient natural language recognition
Solution Approach 1:
The voice recognition system is divided into two segments: a local apparatus module that handles initial voice input and basic processing, and a remote server system that performs comprehensive natural language recognition and algorithm updates. This segmentation allows the local module to maintain fast response for simple operations while the server provides advanced natural language processing capabilities.
Solution Approach 2:
A communication module serves as an intermediary between the local apparatus and the remote server, transmitting voice commands and algorithm update data. This intermediary enables the local apparatus to leverage server-based processing power without requiring significant computational resources locally, resolving the contradiction between local response speed and remote processing capability.
2Measurement precision
If advanced voice recognition algorithms are implemented locally, then recognition accuracy is improved, but system resource consumption increases beyond what individual apparatus modules can provide
Solution Approach 1:
The computationally intensive voice recognition algorithms are extracted from the local apparatus module and relocated to a remote server system. The local module retains only the essential functions of capturing voice input and communicating with the server, thereby achieving high recognition accuracy through server-based processing while keeping local resource consumption minimal.
Solution Approach 2:
The system uses communication modules to transmit voice commands and algorithm data between the local apparatus and remote server. This copying mechanism allows the local apparatus to access and utilize advanced recognition algorithms hosted on the server without duplicating the heavy computational infrastructure locally.
3Measurement precision
If voice recognition algorithms are customized for individual users, then user-specific recognition accuracy is improved, but the complexity of managing and updating algorithms across multiple devices increases
Solution Approach 1:
The remote server system serves multiple functions: it stores voice recognition algorithms, processes voice commands from multiple apparatuses, and manages updates for all connected devices. This universal server-based approach enables user-specific customization without requiring each individual apparatus to have separate algorithm management capabilities, thereby reducing overall system complexity.
Solution Approach 2:
The system implements a feedback mechanism where the server receives voice commands from the apparatus, processes them using updated algorithms, and sends back both the recognition results and updated algorithm versions. This feedback loop allows continuous improvement of user-specific recognition accuracy while the server automatically manages the complexity of algorithm updates across all connected devices.
Data Source
AI summary
Disclosed is an artificial intelligence voice recognition apparatus including: a microphone configured to receive a voice command; a memory configured to store a first voice recognition algorithm; a communication module configured to transmit the voice command to a server system and receive first voice recognition algorithm-related update data from the server system; and a controller configured to perform control to update the first voice recognition algorithm, which is stored in the memory, based on the first voice recognition algorithm-related update data. Accordingly, the voice recognition apparatus is able to provide a voice recognition algorithm fitting to a user's characteristics.