ExKaldi-RT: A Real-Time Automatic Speech Recognition Extension Toolkit of Kaldi
ExKaldi-RT: A Real-Time Automatic Speech Recognition Extension Toolkit of Kaldi
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DOI：
10.1109/gcce53005.2021.9621992
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发表时间：
2021-04
期刊：
影响因子：
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通讯作者：
Yu Wang;Chee Siang Leow;A. Kobayashi;T. Utsuro;H. Nishizaki
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文献类型：
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作者：
Yu Wang;Chee Siang Leow;A. Kobayashi;T. Utsuro;H. Nishizaki
介绍了基于Kaldi自动语音识别工具包和Python语言实现的ExKaldi-RT在线自动语音识别工具包。ExKaldi-RT提供用于构建在线识别管道的工具。虽然类似的工具可以在Kaldi上构建，但ExKaldi-RT的一个关键功能是它可以在Python上工作，它具有易于使用的界面，允许在线ASR系统开发人员开发原创研究，例如通过应用基于神经网络的信号处理和解码使用深度学习框架训练的模型。在最小LibriSpeech语料库上进行了基准实验，实验结果表明ExKaldi-RT在实时识别中具有较好的ASR性能。
This paper describes the ExKaldi-RT online automatic speech recognition (ASR) toolkit that is implemented based on the Kaldi ASR toolkit and Python language. ExKaldi-RT provides tools for building online recognition pipelines. While similar tools are available built on Kaldi, a key feature of ExKaldi-RT that it works on Python, which has an easy-to-use interface that allows online ASR system developers to develop original research, such as by applying neural network-based signal processing and by decoding model trained with deep learning frameworks. We performed benchmark experiments on the minimum LibriSpeech corpus, and it showed that ExKaldi-RT could achieve competitive ASR performance in real-time recognition.