Improving the Lwazi ASR Baseline

Charl van Heerden, Neil Kleynhans, Marelie Davel


We investigate the impact of recent advances in speech recognition techniques for under-resourced languages. Specifically, we review earlier results published on the Lwazi ASR corpus of South African languages, and experiment with additional acoustic modeling approaches. We demonstrate large gains by applying current state-of-the-art techniques, even if the data itself is neither extended nor improved. We analyze the various performance improvements observed, report on comparative performance per technique — across all eleven languages in the corpus — and discuss the implications of our findings for under-resourced languages in general.


DOI: 10.21437/Interspeech.2016-1412

Cite as

Heerden, C.v., Kleynhans, N., Davel, M. (2016) Improving the Lwazi ASR Baseline. Proc. Interspeech 2016, 3534-3538.

Bibtex
@inproceedings{Heerden+2016,
author={Charl van Heerden and Neil Kleynhans and Marelie Davel},
title={Improving the Lwazi ASR Baseline},
year=2016,
booktitle={Interspeech 2016},
doi={10.21437/Interspeech.2016-1412},
url={http://dx.doi.org/10.21437/Interspeech.2016-1412},
pages={3534--3538}
}