PyHTK: Python Library and ASR Pipelines for HTK
Chao Zhang, Florian L. Kreyssig, Qiujia Li, Philip C. Woodland
Abstract
This paper describes PyHTK, which is a Python-based library and associated pipeline to facilitate the construction of large-scale complex automatic speech recognition (ASR) systems using the hidden Markov model toolkit (HTK). PyHTK can be used to generate sophisticated artificial neural network (ANN) models with versatile architectures by converting a compact configuration file defining the ANN, into the form used by HTK tools, as well as supporting a range of capabilities to train and test ANN models. The ASR pipeline is divided into multiple steps, which can be arranged and customised for different ASR data sets, and allows for both step-by-step and fully automatic end-to-end operation. PyHTK is integrated with HTK 3.5.1 which includes an expanded range of ANN layer types and very flexible ways to connect them, together with capabilities for ASR training and testing. Some example systems are included to illustrate the flexibility and performance achievable.
BibTeX
@inproceedings{icassp2019_pyhtkpythonlibra,
title = {PyHTK: Python Library and ASR Pipelines for HTK},
author = {Chao Zhang and Florian L. Kreyssig and Qiujia Li and Philip C. Woodland},
booktitle = {ICASSP 2019},
year = {2019}
}