Implementation of automatic speech recognition (ASR) system to the real scenarios has been discovered many difficulties in two main topics: processing time and resource demands. These obstructions are such big issues in deploying ASR system. This paper proposed three approaches to deal with those problems, which are applying multithread processing to separate sub-processes, exploiting multiplexing and demultiplexing technique to network socket, and improving the distribution of speech recognition engine in audio streaming. In the experiment, we evaluated our approaches with two types of speech input (audio files and audio streams). The results showed that our approaches are using fewer resources (sharing working memory) and also reduce the processing time since the real-time factor (RTF) is reduced by 15 % approximately comparing with the baseline system.
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Distributing and Sharing Resources for Automatic Speech Recognition Applications
Semantic Scholar · Computer Science · 2019
Abstract
Implementation of automatic speech recognition (ASR) system to the real scenarios has been discovered many difficulties in two main topics: processing time and resource demands. These obstructions are such big issues in deploying ASR system. This paper proposed three approaches to deal with those problems, which are applying multithread processing to separate sub-processes, exploiting multiplexing and demultiplexing technique to network socket, and improving the distribution of speech recognition engine in audio streaming. In the experiment, we evaluated our approaches with two types of speech input (audio files and audio streams). The results showed that our approaches are using fewer resources (sharing working memory) and also reduce the processing time since the real-time factor (RTF) is reduced by 15 % approximately comparing with the baseline system.