Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-10T14:18:00.016Z Has data issue: false hasContentIssue false

Using morphemes in language modeling and automatic speech recognition of Amharic

Published online by Cambridge University Press:  12 December 2012

MARTHA YIFIRU TACHBELIE
Affiliation:
School of Information Sciences, Addis Ababa University, Addis Ababa, Ethiopia e-mail: marthayifiru@yahoo.com, solomon_teferra_7@yahoo.com
SOLOMON TEFERRA ABATE
Affiliation:
School of Information Sciences, Addis Ababa University, Addis Ababa, Ethiopia e-mail: marthayifiru@yahoo.com, solomon_teferra_7@yahoo.com
WOLFGANG MENZEL
Affiliation:
Department of Informatics, University of Hamburg, Hamburg, Germany e-mail: menzel@informatik.uni-hamburg.de

Abstract

This paper presents morpheme-based language models developed for Amharic (a morphologically rich Semitic language) and their application to a speech recognition task. A substantial reduction in the out of vocabulary rate has been observed as a result of using subwords or morphemes. Thus a severe problem of morphologically rich languages has been addressed. Moreover, lower perplexity values have been obtained with morpheme-based language models than with word-based models. However, when comparing the quality based on the probability assigned to the test sets, word-based models seem to fare better. We have studied the utility of morpheme-based language models in speech recognition systems and found that the performance of a relatively small vocabulary (5k) speech recognition system improved significantly as a result of using morphemes as language modeling and dictionary units. However, as the size of the vocabulary increases (20k or more) the morpheme-based systems suffer from acoustic confusability and did not achieve a significant improvement over a word-based system with an equivalent vocabulary size even with the use of higher order (quadrogram) n-gram language models.

Type
Articles
Copyright
Copyright © Cambridge University Press 2012 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Abate, S. T. 2006. Automatic Speech Recognition for Amharic. PhD. thesis. University of Hamburg.Google Scholar
Abate, S. T., Menzel, W., and Tafila, B. 2005. An Amharic speech corpus for large vocabulary continuous speech recognition. In Proceedings of 9th European Conference on Speech Communication and Technology, Interspeech-2005, Lisbon, Portugal, pp. 1601–4.Google Scholar
Adafre, S. F. 2005. Part of speech tagging for Amharic using conditional random fields. In Proceedings of the ACL Workshop on Computational Approaches to Semitic Languages, Ann Arbor, Michigan, USA, pp. 4754.Google Scholar
Alemayehu, N., and Willett, P. 2002. Stemming of amharic words for information retrieval. Literary and Linguistic Computing 17 (1): 117.Google Scholar
Amsalu, S., and Gibbon, D. 2005. Finite state morphology of Amharic. In Proceedings of International Conference on Recent Advances in Natural Language Processing, Borovets, Bulgaria, pp. 4751.Google Scholar
Argaw, A. A., and Asker, L. 2007 An amharic stemmer: reducing words to their citation forms. In Proceedings of the Workshop on Computational Approaches to Semitic Languages: Common Issues and Resources - ACL 2007, Prague, Czech Republic, pp. 104–10.Google Scholar
Badr, I., Zbib, R., and Glass, J.. 2008. Segmentation for English-to-Arabic statistical machine translation. In Proceedings of ACL-08, HLT Short Paper, Columbus, Ohio State, pp. 153–6.Google Scholar
Bayou, A. 2000. Developing Automatic Word Parser for Amharic Verbs and their Derivation. Master's thesis, Addis Ababa University.Google Scholar
Bayu, T. 2002. Automatic Morphological Analyzer for Amharic: An Experiment Employing Unsupervised Learning and Autosegmental Analysis Approaches. Master's thesis, Addis Ababa University.Google Scholar
Bender, M., Bowen, J., Cooper, R., and Ferguson, C. 1976. Languages in Ethiopia. London: Oxford University Press.Google Scholar
Bouwman, G., Cranen, B., and Boves, L. 2004. Predicting word correct rate from acoustic and linguistic confusability. In Proceeding the 8th International Conference on Spoken Language Processing, Jeju Island, Korea, pp. 1481–4.Google Scholar
Chen, S. F., and Goodman, J. 1998. An empirical study of smoothing techniques for language modeling. Technical Report TR-10-98, Computer Science Group, Harvard University.Google Scholar
Creutz, M. 2006. Induction of the Morphology of Natural language: Unsupervised Morpheme Segmentation with Application to Automatic Speech Recognition. PhD thesis, Helsinki University of Technology.Google Scholar
Creutz, M., Hirsimäki, T., Kurimo, M., Puurula, A., Pylkkönen, J., Siivola, V., Varjokallio, M., Arisoy, E., Saraçlar, M., and Stolcke, A. 2007. Analysis of morph-based speech recognition and the modeling of out-of-vocabulary words across languages. In Proceedings of NAACL HLT 2007, Rochester, NY, USA, pp. 380–7.Google Scholar
Creutz, M., and Lagus, K. 2005. Unsupervised morpheme segmentation and morphology induction from text corpora using Morfessor 1.1. Technical Report A81, Neural Networks Research Center, Helsinki University of Technology.Google Scholar
Creutz, M., and Lind, K. 2004. Morpheme Segmentation Gold Standards for Finnish and English. Technical Report A77, Helsinki University of Technology.Google Scholar
El-Desoky, A., Gollan, C., Rybach, D., Schlüter, R., and Ney, H. 2009. Investigating the use of morphological decomposition and diacritization for improving arabic LVCSR. In Proceedings of INTERSPEECH 2009, Brighton, UK, pp. 2679–82.Google Scholar
Finke, M., Geutner, P., Hild, H., Kemp, T., Ries, K., and Westphal, M. 1997. The Karlsruhe - Verbmobil speech recognition engine. Proceedings of International Conference on Acoustic, Speech, and Signal Processing, ICASSP 1997 1: 83–6.Google Scholar
Fissaha, S., and Haller, J. 2003. Amharic verb lexicon in the context of machine translation. Proceedings of the 10th Conference on Traitement Automatique des Langues Naturelles, Butz-sur-Mer, France, 2: 183–92.Google Scholar
Gasser, M. 2011. Hornmorpho: a system for morphological processing of Amharic, Oromo, and Tigrinya. In Proceedings of the Conference on Human Language Technology for Development - HLTD 2011, Alexandria, Egypt, pp. 94–9.Google Scholar
Geutner, P. 1995. Using morphology towards better large-vocabulary speech recognition systems. Proceedings of IEEE International on Acoustics, Speech and Signal Processing 1: 445–8.Google Scholar
Heintz, I. 2010. Arabic Language Modeling with Stem-derived Morphemes for Automatic Speech Recognition. PhD thesis, Graduate Program in Linguistics, The Ohio State University.Google Scholar
Hirsimäki, T., Creutz, M., Siivola, V., and Kurimo, M. 2005. Morphologically motivated language models in speech recognition. In Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning, Espoo, Finland, pp. 121–6.Google Scholar
Ircing, P., Krebc, P., Hajič, J., Psutka, J., Khudanpur, S., Jelinek, F., and Byrne, W., 2001. On large vocabulary continuous speech recognition of highly inflectional language - Czech. In Proceeding of the European Conference on Speech Communication and Technology, Aalborg, Denmark, pp. 487–9.Google Scholar
Junqua, J. C., and Haton, J. P.. 1996. Robustness in Automatic Speech Recognition: Fundamentals and Applications. London: Kluwer Academic.Google Scholar
Kirchhoff, K., Bilmes, J., Henderson, J., Schwartz, R., Noamany, M., Schone, P., Ji, G., Das, S., Egan, M., He, F., Vergyri, D., Liu, D., and Duta, N. 2002. Novel speech recognition models for Arabic. Technical Report, Johns-Hopkins University Summer Research Workshop.Google Scholar
Labaka, G., Stroppa, N., Way, A., and Sarasola, K. 2007. Comparing rule-based and data-driven approaches to spanish-to-banque machine translation. In Proceedings of Machine Translation Summit XI, 2007, Copenhagen, Denmark.Google Scholar
Manning, C. D., and Schütze, H. 1999. Foundations of Statistical Natural Language Processing. Cambridge and London: The MIT Press.Google Scholar
Oflazer, K. 2008. Statistical machine translation into a morphologically complex language. In Proceedings of the 9th International Conference on Computational Linguistics and Intelligent Text Processing CICLing’08, Haifa, Israel. Published as LNCS vol. 4919, pp. 376–87.Google Scholar
Pellegrini, T., and Lamel, L. 2006. Investigating automatic decomposition for ASR in less represented languages. In Proceedings of INTERSPEECH 2006, Pittsburgh, Pennsylvania, USA, pp. 285–8.Google Scholar
Pellegrini, T., and Lamel, L. 2007. Using phonetic features in unsupervised word decompounding for ASR with application to a less-represented language. In Proceedings of INTERSPEECH 2007, pp. 1797–1800.Google Scholar
Pellegrini, T., and Lamel, L. 2009. Automatic word decompounding for ASR in a morpholo- gically rich language: application to amharic. IEEE Transactions on Audio, Speech, and Language Processing 17 (5): 863–73.Google Scholar
Sproat, R. 1992. Morphology and Computation. London: The MIT Press.Google Scholar
Stolcke, A. 2002. SRILM – an extensible language modeling toolkit. Proceedings of International Conference on Spoken Language Processing 2: 901–4.Google Scholar
Tachbelie, M. Y. 2010. Morphology-Based Language Modeling for Amharic. PhD thesis, University of Hamburg. http://www2.sub.uni-hamburg.de/opus/volltexte/2010/4848/pdf/TachbelieDissertation.pdf. Last accessed on the 3rd of December, 2012.Google Scholar
Tachbelie, M. Y., and Menzel, W. 2009. Morpheme-based language modeling for inflectional language – Amharic. In Nicolov, N., Angelova, G., and Mitkov, R. (eds.), Recent Advances in Natural Language Processing V, Current Issues in Linguistic Theory, pp. 301–10. Amsterdam and Philadelphia: John Benjamin's Publishing.Google Scholar
Teferra, A., and Hudson, G. 2007. Essentials of Amharic. Köln: Köppe.Google Scholar
Voigt, R. M. 1987. The classification of central semitic. Journal of Semitic Studies 32: 121.Google Scholar
Vergyri, D., Kirchhoff, K., Duh, K., and Stolcke, A. 2004. Morphology-based language modeling for Arabic speech recognition. In Proceedings of International Conference on Spoken Language Processing, Jeju Island, Korea, pp. 2245–8.Google Scholar
Whittaker, E., and Woodland, P. 2000. Particle-based language modeling. In Proceeding of International Conference on Spoken Language Processing, Beijing, China, pp. 170–3.Google Scholar
Yimam, B. 2007. YäamarIña Säwasäw, 2nd ed.Addis Ababa: EMPDE.Google Scholar
Young, S., Evermann, G., Gales, M., Hain, T., Kershaw, D., Liu, X., Moore, G., Odell, J., Ollason, D., Povey, D., Valtchev, V., and Woodland, P. 2006. The HTK Book. Cambridge University, Engineering Department. Cambridge, UK.Google Scholar