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Open Source Speech Recognition on Edge Devices

机译:边缘设备上的开源语音识别

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Deep learning has revived the field of automatic speech recognition (ASR) in the last ten years and pushed recognition rates into regions on par with humans. Applications like Siri, Amazon Alexa and Google Assistant are very popular, but have inherent privacy problems. In this paper, we evaluate state of the art open source ASR models regarding their usability in a smart speaker without cloud, both in terms of accuracy and runtime performance on cost-effective low power edge devices. We found Kaldi to be the most accurate solution and also among the fastest ones. It runs more than fast enough on an Nvidia Jetson Nano. It is still not on par with commercial cloud services, but getting close to it.
机译:深度学习在过去十年中复兴了自动语音识别(ASR)领域,并将识别率推向与人类同等的地区。 Siri,Amazon Alexa和Google Assistant等应用程序非常受欢迎,但存在固有的隐私问题。在本文中,我们就其在无云智能扬声器中的可用性评估了最先进的开源ASR模型,包括在经济高效的低功耗边缘设备上的准确性和运行时性能。我们发现Kaldi是最准确的解决方案,也是最快的解决方案之一。它在Nvidia Jetson Nano上的运行速度足够快。它仍然不能与商业云服务相提并论,但是越来越接近它。

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