LEARNING GREEK PHONETIC RULES USING DECISION-TREE BASED MODELS

Dimitrios P. Lyras, Kyriakos N. Sgarbas, Nikolaos D. Fakotakis

2007

Abstract

This paper describes the application of decision-tree based induction techniques for automatic extraction of phonetic knowledge for the Greek language. We compare the ID3 algorithm and Quinlan’s C4.5 model by applying them to two pronunciation databases. The extracted knowledge is then evaluated quantitatively. In the ten cross-fold validation experiments that are conducted, the decision tree models are shown to produce an accuracy higher than 99.96% when trained and tested on each dataset.

References

  1. Babiniotis, G., 1986. S???pt??? ?st???a t?? ????????? G??ssa?. Athens.
  2. Busser, G., Daelemans, W., Van den Bosch, A., 1999. Machine Learning of word pronunciation: The case against abstraction. In Proc. 6th European Conference on Speech Communication and Technology, Eurospeech 99, Budapest, Hungary, pages 2123-2196.
  3. Chomsky, N., and Halle, M., 1968. The Sound Patterns of English, Harper & Roe, New York.
  4. Dietterich, T.G, 1997. Machine Learning research:Four current directions. AI Magazine, 18(4):97-136.
  5. Johnson, C. D., 1972. Formal Aspects of Phonological Description. Mouton, Hauge.
  6. Levinson, S.E., Liberman, M.Y., Ljolje, A., and Miller, L.G., 1989. Speaker Independent Phonetic Transcription of Fluent Speech for Large Vocabulary Speech Recognition. ICASSP'89, pp. 441-444.
  7. Mitchell, T., “Decision Tree Learning”, in T. Mitchell, Machine Learning, McGraw-Hill, 1997, pp. 52-78.
  8. Nunn, A., van Heuven, V.J., 1993. Morphon, lexiconbased text-to-phoneme conversion and phonological rules. In V.J. Van Heuven and L.C.W. Pols, editors, Analysis and synthesis of speech; strategic research towards high-quality text-to-speech generation. Berlin, Mouton de Gruyter.
  9. Petrounias, E., 1984. ?e?e??????? G?aµµat??? ?a? S?????t??? ?????s?. University Studio Press, Thessaloniki, Greece.
  10. Quinlan, J. R., 1993. C4.5: Programs for Machine Learning. San Mateo: Morgan Kaufmann Publishers.
  11. Rentzepopoulos, P., and Kokkinakis, G., 1996. Efficient Multilingual Phoneme-to-Grapheme Conversion Based on HMM. Computational Linguistics, 22:3.
  12. Robins, R. H., 1980. General Linguistics. An Introductory Survey. 3rd Edition, Longman.
  13. Rosenberg, C. R., 1987. Revealing the Structure of NETtalk's Internal Representations. In Proc. of the 9th Annual Conf. Cognitive Science Society, pp.537-554.
  14. Sejnowski, T.J., Rosenberg, C.S., 1987. Parallel networks that learn to pronounce English text. Complex Systems, 1:145-168.
  15. Setatos, M., 1974. F???????a t?? ?????? ?e?e????????, Papazisis, Athens.
  16. Sgarbas, K., Fakotakis, N., and Kokkinakis, G., 1995. A PC-KIMMO-based Morphological Description of Modern Greek. Lit. & Ling. Computing, 10:189-201.
  17. Sgarbas, K., Fakotakis, N., and Kokkinakis, G., 1998. A PC-KIMMO-based Bi-directional Graphemic/ Phonetic Converter for Modern Greek. Literary and Linguistic Computing, Oxford University Press, Vol.13,No.2, pp. 65-75.
  18. Sgarbas, K., Fakotakis, N., 2005. A Revised Phonetic Alphabet for Modern Greek. In Proceedings of SPECOM 2005, 10th International Conference on Speech and Computer, 17-19 October 1005, Patras, Greece, pp.273-276.
  19. Triantafyllidis, M., 1977. ?e?e??????? G?aµµat???. ????, Athens.
  20. Van den Bosch, A., Daelemans, W, 1993. Data-Oriented Methods for Grapheme-to-Phoneme Conversion. Proceedings of EACL, Utrecht, 45-53.
  21. Winston, P., Learning by Building Identification Trees, in P. Winston, 1992. Artificial Intelligence, AddisonWesley Publishing Company, pp.423-442.
  22. Witten, I., Frank, E., 2005. Data Mining: Practical Machine Learning tools and techniques, 2nd Edition, Morgan Kaufmann, San Francisco.
  23. Xuedong, H., Acero, A., Alleva, F., Hwang, M.-Y., Jiang, L., and Mahajan, M., 1995. Microsoft Windows Highly Intelligent Speech Recognizer: WHISPER. ICASSP'95, USA.
Download


Paper Citation


in Harvard Style

P. Lyras D., N. Sgarbas K. and D. Fakotakis N. (2007). LEARNING GREEK PHONETIC RULES USING DECISION-TREE BASED MODELS . In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-972-8865-89-4, pages 424-427. DOI: 10.5220/0002381204240427


in Bibtex Style

@conference{iceis07,
author={Dimitrios P. Lyras and Kyriakos N. Sgarbas and Nikolaos D. Fakotakis},
title={LEARNING GREEK PHONETIC RULES USING DECISION-TREE BASED MODELS},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2007},
pages={424-427},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002381204240427},
isbn={978-972-8865-89-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - LEARNING GREEK PHONETIC RULES USING DECISION-TREE BASED MODELS
SN - 978-972-8865-89-4
AU - P. Lyras D.
AU - N. Sgarbas K.
AU - D. Fakotakis N.
PY - 2007
SP - 424
EP - 427
DO - 10.5220/0002381204240427