  The availability of open-source software is playing a remarkable role in
automatic speech recognition (ASR). Kaldi, for instance, is widely used to
develop state-of-the-art offline and online ASR systems. This paper describes
the "ExKaldi-RT," online ASR toolkit implemented based on Kaldi and Python
language. ExKaldi-RT provides tools for providing a real-time audio stream
pipeline, extracting acoustic features, transmitting packets with a remote
connection, estimating acoustic probabilities with a neural network, and online
decoding. While similar functions are available built on Kaldi, a key feature
of ExKaldi-RT is completely working on Python language, which has an
easy-to-use interface for online ASR system developers to exploit original
research, for example, by applying neural network-based signal processing and
acoustic model trained with deep learning frameworks. We performed benchmark
experiments on the minimum LibriSpeech corpus, and showed that ExKaldi-RT could
achieve competitive ASR performance in real-time.
