Hybrid Speech Recognition System for Mobile Devices
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Solution Overview
Problem
Mobile devices face limitations in performing complex speech recognition tasks due to limited computational, memory, and battery resources, leading to delayed user experiences as these tasks are often offloaded to network servers, preventing users from viewing query results based on local data and causing significant delays.
Innovation Solution
A method and system that enables voice commands on client devices by translating audio streams into machine-readable commands using local speech recognizers, querying both local and remote databases simultaneously, and displaying results on the device, allowing for concurrent processing and display of query results from both sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If speech recognition tasks are offloaded to network servers, then speech recognition accuracy is improved, but response time deteriorates
Solution Approach 1:
The speech recognition system is segmented into two parts: a lightweight recognizer embedded in the mobile device for immediate local recognition, and a comprehensive recognizer on the network server for accurate complex task recognition. This segmentation allows simple commands to be processed locally (fast response) while complex commands are handled by the server (high accuracy), resolving the contradiction between speed and accuracy.
2Adaptability or versatility
If speech recognition tasks are performed on network servers, then recognition capability is improved, but user experience deteriorates due to delay
Solution Approach 1:
The system performs preliminary speech recognition action locally on the mobile device before potentially involving the network server. The embedded recognizer immediately processes the speech input and provides preliminary results, so users don't have to wait for server processing. This preliminary local action improves user experience by providing immediate feedback while maintaining the server's comprehensive recognition capability.
3Loss of time
If speech recognition is performed locally on mobile devices, then response time is improved, but recognition accuracy deteriorates
Solution Approach 1:
The system dynamically determines whether to use the embedded recognizer or the network server recognizer based on the complexity of the speech task. Simple commands are processed locally by the embedded recognizer for fast response, while complex commands are transferred to the network server for accurate recognition. This dynamic adaptation resolves the contradiction by optimizing the recognition path based on real-time requirements.
Data Source
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AI summary
A method, computer program product, and system are provided for performing a voice command on a client device. The method can include translating, using a first speech recognizer located on the client device, an audio stream of a voice command to a first machine-readable voice command and generating a first query result using the first machine-readable voice command to query a client database. In addition, the audio stream can be transmitted to a remote server device that translates the audio stream to a second machine-readable voice command using a second speech recognizer. Further, the method can include receiving a second query result from the remote server device, where the second query result is generated by the remote server device using the second machine-readable voice command and displaying the first query result and the second query result on the client device.