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Authors: Alexander Gutkin and Simon King

Affiliation: Centre for Speech Technology Research, University of Edinburgh, United Kingdom

Abstract: This paper deals with formulation of alternative structural approach to the speech recognition problem. In this approach, we require both the representation and the learning algorithms defined on it to be linguistically meaningful, which allows the speech recognition system to discover the nature of the linguistic classes of speech patterns corresponding to the speech waveforms. We briefly discuss the current formalisms and propose an alternative — a phonologically inspired string-based inductive speech representation, defined within an analytical framework specifically designed to address the issues of class and object representation. We also present the results of the phoneme classification experiments conducted on the TIMIT corpus of continuous speech.

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Paper citation in several formats:
Gutkin, A. and King, S. (2005). Inductive String Template-Based Learning of Spoken Language. In Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems (ICEIS 2005) - PRIS; ISBN 972-8865-28-7, SciTePress, pages 43-51. DOI: 10.5220/0002568800430051

@conference{pris05,
author={Alexander Gutkin. and Simon King.},
title={Inductive String Template-Based Learning of Spoken Language},
booktitle={Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems (ICEIS 2005) - PRIS},
year={2005},
pages={43-51},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002568800430051},
isbn={972-8865-28-7},
}

TY - CONF

JO - Proceedings of the 5th International Workshop on Pattern Recognition in Information Systems (ICEIS 2005) - PRIS
TI - Inductive String Template-Based Learning of Spoken Language
SN - 972-8865-28-7
AU - Gutkin, A.
AU - King, S.
PY - 2005
SP - 43
EP - 51
DO - 10.5220/0002568800430051
PB - SciTePress