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Robust voice recognition as a distributed service

机译:强大的语音识别作为分布式服务

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Current voice recognition systems tend to be implemented as embedded proprietary solutions. This model is not suitable for the growing complexities of present and future developments: It is single-user, it is non portable, and it assumes the workstation model, where all the CPU resources are supposed to he locally available. This work researches how a high performance speech recognition system can be redesigned and implemented as a time-critical network service with three main design goals: Scalability, predictability and POSIX portability. The whole idea has been tested by rebuilding IVORY, a well known robust desktop voice recognition methodology, as a distributed service. Also, potential fields of application are identified.
机译:当前的语音识别系统倾向于被实现为嵌入式专有解决方案。该模型不适用于当前和未来发展中日益增长的复杂性:它是单用户的,它是非便携式的,并且它假定是工作站模型,在该模型中所有CPU资源都应在本地使用。这项工作研究如何将高性能语音识别系统重新设计和实现为具有时间紧迫性的网络服务,并具有三个主要设计目标:可伸缩性,可预测性和POSIX可移植性。整个构想已经通过将IVORY(一种众所周知的健壮的桌面语音识别方法)重建为分布式服务进行了测试。而且,确定了潜在的应用领域。

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