Asynchronously Parallel Decoding For Automatic Speech Recognition Services

Nattapong Kurpukdee, Surasak Boonkla, P. Sertsi, Vataya Chunwijitra
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Abstract

We proposed a new automatic speech recognition (ASR) service architecture that is extendable to medium-scale ASR service and more flexible than the previous architecture. Improvement aims to substitute the distributed processing approach with an asynchronous parallel thread for decoding multiple voice streams. We replace our TCP-based communication protocol with a remote procedure call developed by Google (gRPC) that makes our ASR service become a developer-friendly, less overhead connection. Besides, the API gateway is employed to reinforce the ASR services by multiple servers so that we can increase our new ASR service to a larger scale. The experimental result shows that our new architecture performs faster than the previous architecture in terms of real-time factor.
用于自动语音识别服务的异步并行解码
提出了一种新的自动语音识别(ASR)服务体系结构,该体系结构可扩展到中等规模的自动语音识别服务,并且比以前的体系结构更具灵活性。改进的目的是用异步并行线程代替分布式处理方法来解码多个语音流。我们用Google (gRPC)开发的远程过程调用取代了基于tcp的通信协议,这使得我们的ASR服务成为开发人员友好的、开销更少的连接。此外,API网关通过多台服务器加强ASR服务,使我们的新ASR服务规模更大。实验结果表明,我们的新架构在实时性方面比以前的架构要快。
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