Hybrid Controller for ASR Latency and Accuracy Trade-off
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Solution Overview
Problem
Existing automatic speech recognition (ASR) systems on mobile devices face challenges in efficiently determining when to offload speech recognition processing to a remote server and selecting the appropriate speech representation type based on bandwidth characteristics, leading to suboptimal performance and resource management.
Innovation Solution
A local controller on the mobile device determines the remote ASR processing condition and transforms the speech input signal into one of multiple representation types, such as ASR feature vectors, lossy compressed speech, or uncompressed speech, to send to a remote server for processing, while continuing local ASR processing and adapting based on factors like recognition confidence, network conditions, and latency characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If speech recognition is performed locally on the mobile device, then processing speed and latency are improved, but recognition accuracy and resource management deteriorate due to limited device capabilities
Solution Approach 1:
The ASR system is segmented into local and remote components. The local mobile device performs initial speech processing and feature extraction, while the remote server handles complex recognition tasks. This segmentation allows the system to leverage both the speed of local processing and the accuracy of remote processing resources.
Solution Approach 2:
A hybrid controller acts as an intermediary between the local ASR arrangement and the remote server. It dynamically determines whether to send speech inputs to the remote server based on confidence scores, network conditions, and other factors, thereby coordinating between local and remote processing to optimize both latency and accuracy.
2Reliability
If speech recognition is performed remotely on the server, then recognition accuracy is improved, but network bandwidth consumption and processing latency worsen
Solution Approach 1:
The system performs partial speech processing locally before potentially transmitting to the remote server. By extracting features and performing preliminary processing locally, the system reduces the amount of data that needs to be transmitted over the network, thereby reducing bandwidth consumption while still leveraging remote resources for improved accuracy when needed.
Solution Approach 2:
The hybrid controller dynamically changes transmission parameters based on network conditions, confidence scores, and speech characteristics. It adjusts whether to transmit raw speech signals, processed features, or no data at all, thereby optimizing network bandwidth usage based on current system state and requirements.
3Reliability
If multiple speech representation types are transmitted to the remote server, then recognition accuracy is improved, but device complexity and processing overhead increase
Solution Approach 1:
The system dynamically selects which speech representation types to generate and transmit based on current conditions such as network bandwidth availability, speech characteristics, and confidence scores. Rather than always generating all possible representation types, the system adapts its processing complexity to match current requirements, thereby reducing overall device complexity while maintaining accuracy when needed.
4Productivity
If local ASR processing is enhanced to improve autonomy, then processing speed is improved, but device resources and power consumption worsen
Solution Approach 1:
The local ASR arrangement performs self-service by handling speech processing tasks that can be completed locally without consuming excessive resources. The hybrid controller monitors resource usage and automatically determines when to handle speech independently and when to offload to the remote server, allowing the system to maintain processing speed while managing power consumption through intelligent self-regulation.
Data Source
AI summary
A mobile device is described which is adapted for automatic speech recognition (ASR). A speech input receives an unknown speech input signal from a user. A local controller determines if a remote ASR processing condition is met, transforms the speech input signal into a selected one of multiple different speech representation types, and sends the transformed speech input signal to a remote server for remote ASR processing. A local ASR arrangement performs local ASR processing of the speech input including processing any speech recognition results received from the remote server.