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.
Cite
@article{arxiv.2104.01384,
title = {ExKaldi-RT: A Real-Time Automatic Speech Recognition Extension Toolkit of Kaldi},
author = {Yu Wang and Chee Siang Leow and Akio Kobayashi and Takehito Utsuro and Hiromitsu Nishizaki},
journal= {arXiv preprint arXiv:2104.01384},
year = {2021}
}
Comments
Accepted at the IEEE 10th Global Conference on Consumer Electronics