Distributing and Sharing Resources for Automatic Speech Recognition Applications

2019 22nd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA) Pub Date : 2019-10-01 DOI:10.1109/O-COCOSDA46868.2019.9041201

Sila Chunwijitra, Surasak Boonkla, Vataya Chunwijitra, Nattapong Kurpukdee, P. Sertsi, S. Kasuriya

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引用次数: 2

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.

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自动语音识别应用程序的资源分配和共享

在实际场景中实现自动语音识别(ASR)系统存在着处理时间和资源需求两个主要问题。这些障碍是部署ASR系统的大问题。针对这些问题，本文提出了三种解决方法:将多线程处理应用于分离子进程，将多路复用和解路复用技术应用于网络套接字，以及改进音频流中语音识别引擎的分布。在实验中，我们用两种类型的语音输入(音频文件和音频流)评估了我们的方法。结果表明，我们的方法使用更少的资源(共享工作内存)，并且还减少了处理时间，因为实时因子(RTF)与基线系统相比减少了大约15%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2019 22nd Conference of the Oriental COCOSDA International Committee for the Co-ordination and Standardisation of Speech Databases and Assessment Techniques (O-COCOSDA)

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