@inproceedings{,
author={T{\'o}th, L{\'a}szl{\'o} and Kocsor, Andr{\'a}s and Kov{\'a}cs, Korn{\'e}l},
title={A Discriminative Segmental Speech Model and its Application to Hungarian
Number Recognition},
abstract={This paper presents a stochastic segmental speech recogniser that models
the a posteriori probabilities directly. The main issues concerning the
system are segmental phoneme classification, utterance-level aggregation
and the pruning of the search space. For phoneme classification, artificial
neural networks and support vector machines are applied. Phonemic segmentation
and utterance-level aggregation is performed with the aid of anti-phoneme
modelling. At the phoneme level, the system convincingly outperforms the
HMM system trained on the same corpus, while at the word level it attains
the performance of the HMM system trained without embedded training. },
booktitle={Text, Speech and Dialogue: Third International Workshop, TSD 2000, LNAI
vol. 1902},
year={2000},
month={September},
publisher={Springer-Verlag GmbH},
address={Brno, Czech Republic},
editor={P. Sojka, I. Kopecek, K. Pala},
pages={307-313}
}