# ExKaldi-RT: A Real-Time Automatic Speech Recognition Extension Toolkit of Kaldi

arXiv: https://arxiv.org/abs/2104.01384 · HTML: https://mlsanity.com/paper/2104.01384/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 28 references that are in the map.
- First posted on arXiv 3 Apr 2021.

## Builds on (most cited first, 6 of 6)

- [Streaming End-to-end Speech Recognition For Mobile Devices](https://mlsanity.com/paper/1811.06621/) (2018)
- [Jasper: An End-to-End Convolutional Neural Acoustic Model](https://mlsanity.com/paper/1904.03288/) (2019)
- [RWTH ASR Systems for LibriSpeech: Hybrid vs Attention -- w/o Data Augmentation](https://mlsanity.com/paper/1905.03072/) (2019)
- [The PyTorch-Kaldi Speech Recognition Toolkit](https://mlsanity.com/paper/1811.07453/) (2018)
- [Low Latency End-to-End Streaming Speech Recognition with a Scout Network](https://mlsanity.com/paper/2003.10369/) (2020)
- [PyKaldi2: Yet another speech toolkit based on Kaldi and PyTorch](https://mlsanity.com/paper/1907.05955/) (2019)

## Abstract (arXiv)

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.