ISCA Archive ICSLP 2000
ISCA Archive ICSLP 2000

A comparison of data-derived and knowledge-based modeling of pronunciation variation

Mirjam Wester, Eric Fosler-Lussier

This paper focuses on modeling pronunciation variation in two different ways: data-derived and knowledge-based. The knowledge-based approach consists of using phonological rules to generate variants. The data-derived approach consists of performing phone recognition, followed by various pruning and smoothing methods to alleviate some of the errors in the phone recognition. Using phonological rules led to a small improvement in WER; whereas, using a data-derived approach in which the phone recognition was smoothed using simple decision trees (d-trees) prior to lexicon generation led to a significant improvement compared to the baseline. Furthermore, we found that 10% of variants generated by the phonological rules were also found using phone recognition, and this increased to 23% when the phone recognition output was smoothed by using d-trees. In addition, we propose a metric to measure confusability in the lexicon and we found that employing this confusion metric to prune variants results in roughly the same improvement as using the d-tree method.


Cite as: Wester, M., Fosler-Lussier, E. (2000) A comparison of data-derived and knowledge-based modeling of pronunciation variation. Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000), vol. 1, 270-273

@inproceedings{wester00_icslp,
  author={Mirjam Wester and Eric Fosler-Lussier},
  title={{A comparison of data-derived and knowledge-based modeling of pronunciation variation}},
  year=2000,
  booktitle={Proc. 6th International Conference on Spoken Language Processing (ICSLP 2000)},
  pages={vol. 1, 270-273}
}