Unsupervised models for morpheme segmentation and morphology learning

ACM Transactions on Speech and Language Processing

Volumn 4, Issue 1, 2007, Pages

  Creutz, Mathias ^a   Lagus, Krista ^a  

^a AALTO UNIVERSITY   (Finland)

Author keywords

Efficient storage; Highly inflecting and compounding languages; Language independent methods; Maximum a posteriori (MAP) estimation; Morpheme lexicon and segmentation; Unsupervised learning

Indexed keywords

HIGHLY INFLECTING AND COMPOUNDING LANGUAGES; LANGUAGE INDEPENDENT METHODS; MAXIMUM A POSTERIORI (MAP) ESTIMATION; MORPHEME LEXICON; UNSUPERVISED LEARNING;

ALGORITHMS; BENCHMARKING; FORMAL LANGUAGES; PARAMETER ESTIMATION; TEXT PROCESSING;

LEARNING SYSTEMS;

EID: 33846987588     PISSN: 15504875     EISSN: 15504883     Source Type: Journal    
DOI: 10.1145/1217098.1217101     Document Type: Article

References (56)

1. ADDA-DECKER, M. 2003. A corpus-based decompounding algorithm for German lexical modeling in LVCSR. In Proceedings of the 8th European Conference on Speech Communication and Technology (Eurospeech). Geneva, Switzerland. 257-260.
2. ALLEN, M., BADECKER, W., AND OSTERHOUT, L. 2003. Morphological analysis in sentence processing: An ERP study. Lang. Cognit. Proc. 18, 4, 405-430.
3. ALTUN, Y. AND JOHNSON, M. 2001. Inducing SFA with e-transitions using Minimum Description Length. In Proceedings of the Finite-State Methods in Natural Language Processing, ESSLLI Workshop. Helsinki, Finland.
4. ANDO, R. K. AND LEE, L. 2000. Mostly-unsupervised statistical segmentation of Japanese: Applications to Kanji. In Proceedings of the 6th Applied Natural Language Processing Conference and 1st Meeting of the North American Chapter of the Association for Computational Linguistics (ANLP-NAACL). 241-248.
5. BAAYEN, R. H., PIEPENBROCK, R., AND GULIKERS, L. 1995. The CELEX lexical database (CD-ROM). Linguistic Data Consortium, University of Pennsylvania, Philadelphia, PA. http://wave.ldc. upenn.edu/Catalog/CatalogEntry.Jsp?catalogId=LDC96L14.
6. BAAYEN, R. H. AND SCHREUDER, R. 2000. Towards a psycholinguistic computational model for morphological parsing. Philosophical Transactions of the Royal Society (Series A: Mathematical, Physical and Engineering Sciences 358), 1-13.
7. BARONI, M., MATIASEK, J., AND TROST, H. 2002. Unsupervised learning of morphologically related words based on orthographic and semantic similarity. In Proceedings of the Workshop on Morphological & Phonological Learning of ACL. 48-57.
8. BRENT, M. R. 1999. An efficient, probabilistically sound algorithm for segmentation and word discovery. Machine Learn, 34, 71-105.
9. CHANG, J.-S., LIN, Y.-C., AND Su, K.-Y. 1995. Automatic construction of a Chinese electronic dictionary. In Proceedings of the 3rd Workshop on Very Large Corpora. Somerset, NJ. 107-120.
10. CREUTZ, M. 2003. Unsupervised segmentation of words using prior distributions of morph length and frequency. In Proceedings of the Association for Computations Languages (ACL'03). Sapporo, Japan. 280-287.
11. CREUTZ, M. AND LAGUS, K. 2002. Unsupervised discovery of morphemes. In Proceedings of the Workshop on Morphological and Phonological Learning of ACL. Philadelphia, PA. 21-30.
12. CREUTZ, M. AND LAGUS, K. 2004. Induction of a simple morphology for highly-inflecting languages. In Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology (SIGPHON). Barcelona, Spain. 43-51.
13. CREUTZ, M. AND LAGUS, K. 2005a. Inducing the morphological lexicon of a natural language from unannotated text. In Proceedings of the International and Interdisciplinary Conference on Adaptive Knowledge Representation and Reasoning (AKRR'05). Espoo, Finland. 106-113.
14. CREUTZ, M. AND LAGUS, K. 2005b. Unsupervised morpheme segmentation and morphology induction from text corpora using Morfessor 1.0. Tech. rep. A81, Publications in Computer and Information Science, Helsinki University of Technology.
15. CREUTZ, M. AND LINDÉN, K. 2004. Morpheme segmentation gold standards for Finnish and English. Tech. rep. A77, Publications in Computer and Information Science, Helsinki University of Technology.
16. DE MARCKEN, C. G. 1996. Unsupervised language acquisition. Ph.D. thesis, MIT, Cambridge, MA.
17. DÉJEAN, H. 1998. Morphemes as necessary concept for structures discovery from untagged corpora. Workshop on Paradigms and Grounding in Natural Language Learning. Adelaide, Australia. 295-299.
18. DELIGNE, S. AND BIMBOT, F. 1997. Inference of variable-length linguistic and acoustic units by multigrams. Speech Comm. 23, 223-241.
19. FENG, H., CHEN, K., KIT, C., AND DENG, X. 2004. Unsupervised segmentation of Chinese corpus using accessor variety. In Proceedings of the 1st International Joint Conference on Natural Language Processing (IJCNLP). Sanya, Hainan. 255-261.
20. GAUSSIER, E. 1999. Unsupervised learning of derivational morphology from inflectional lexicons. In Proceedings of the ACL Workshop on Unsupervised Learning in Natural Language Processing. University of Maryland. 24-30.
21. GE, X., PRATT, W., AND SMYTH, P. 1999. Discovering Chinese words from unsegmented text. In Proceedings of SIGIR. 271-272.
22. GOLDSMITH, J. 2001. Unsupervised learning of the morphology of a natural language. Computat. Linguis. 27, 2, 153-198.
23. GOLDSMITH, J. 2005. An algorithm for the unaupervised learning of morphology. Tech. rep. TR-2005-06, Department of Computer Science, University of Chicago. http://humfsl.uchicago. edu/~jagoldsm/Papers/Algorithm.pdf.
24. GOLDSMITH, J. AND Hu, Y. 2004. From signatures to finite state automata. Midwest Computational Linguistics Colloquium, Bloomington IN.
25. HAFER, M. A. AND WEISS, S. F. 1974. Word segmentation by letter successor varieties. Inform. Storage Retriev. 10, 371-385.
26. HAKULINEN, L. 1979. Suomen kielen rakenneja kehitys (The Structure and Development of the Finnish Language) 4th Ed. Kustannus-Oy Otava.
27. HARRIS, Z. S. 1955. From phoneme to morpheme. Language 31, 2, 190-222. (Reprinted 1970 in Papers in Structural and Transformational Linguistics, Reidel Publishing Company, Dordrecht, Holland.)
28. HARRIS, Z. S. 1967. Morpheme boundaries within words: Report on a computer test. Transformations and Discourse Analysis Papers 73. (Reprinted 1970 in Papers in Structural and Transformational Linguistics, Reidel Publishing Company, Dordrecht, Holland.)
29. HU, Y., MATVEEVA, I., GOLDSMITH, J., AND SPRAGUE, C. 2005b. The SED heuristic for morpheme discovery: a look at Swahili. In Proceedings of the 2nd Workshop of Psychocomputational Models of Human Language Acquisition. Ann Arbor, MI. 28-35.
30. HU, Y, MATVEEVA, I., GOLDSMITH, J., AND SPRAGUE, C. 2005a. Using morphology and syntax together in unsupervised learning. In Proceedings of the 2nd Workshop of Psychocomputational Models of Human Language Acquisition. Ann Arbor, MI. 20-27.
31. JACQUEMIN, C. 1997. Guessing morphology from terms and corpora. In Proceedings of the 20th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'97). Philadelphia, PA. 156-165.
32. JÄRVIKIVI, J. AND NIEMI, J. 2002. Form-based representation in the mental lexicon: Priming (with) bound stem allomorphs in Finnish. Brain Lang. 81, 412-423.
33. JOHNSON, H. AND MARTIN, J. 2003. Unsupervised learning of morphology for English and Inuktitut. Human Language Technology and North American Chapter of the Association for Computational Linguistics Conference (HLT-NAACL'03). Edmonton, Canada.
34. KAZAKOV, D. 1997. Unsupervised learning of naïve morphology with genetic algorithms. Workshop Notes of the ECML/MLnet Workshop on Empirical Learning of Natural Language Processing Tasks. Prague, Czech Republic, 105-112.
35. KIT, C. 2003. How does lexical acquisition begin? A cognitive perspective. Cognit. Science 1, 1, 1-50.
36. KIT, C., PAN, H., AND CHEN, H. 2002. Learning case-based knowledge for disambiguating Chinese word segmentation: A preliminary study. In Proceedings of the COLING Workshop SIGHAN-1. Taipei, Taiwan. 33-39.
37. KIT, C. AND WILKS, Y 1999. Unsupervised learning of word boundary with description length gain. la. Proceedings of the CoNLL99ACL Workshop. Bergen, Norway.
38. KNEISSLER, J. AND KLAKOW, D. 2001. Speech recognition for huge vocabularies by using optimized sub-word units. In Proceedings of the 7th European Conference on Speech Communication and Technology (Eurospeech). Aalborg, Denmark. 69-72.
39. KONTOROVICH, L., RON, D., AND SINGER, Y. 2003. A Markov model for the acquisition of morphological structure. Tech. rep. CMU-CS-03-147, School of Computer Science, Carnegie Mellon University.
40. KOSKENNIEMI, K. 1983. Two-level morphology: A general computational model for word-form recognition and production. Ph.D. thesis, University of Helsinki.
41. MATTHEWS, P. H. 1991. Morphology 2nd Ed. Cambridge Textbooks in Linguistics.
42. McKINNON, R., ALLEN, M., AND OSTERHOUT, L. 2003. Morphological decomposition involving nonproductive morphemes: ERP evidence. Cognit. Neurosci, Neuropsychol, 14, 6, 883-886.
43. NAGATA, M. 1997. A self-organizing Japanese word segmenter using heuristic word identification and re-estimation. In Proceedings of the Bth Workshop on Very Large Corpora. 203-215.
44. NEUVEL, S. AND FULOP, S. A. 2002. Unsupervised learning of morphology without morphemes. In Proceedings of the Workshop on Morphological & Phonological Learning of ACL. 31-40.
45. PENG, F. AND SCHUURMANS, D. 2001. Self-supervised Chinese word segmentation. In Proceedings of the 4th International Conference on Intelligent Data Analysis (IDA). Springer, 238-247.
46. QUIRK, R., GREENBAUM, S., LEECH, G., AND SVARTVIK, J. 1985. A Comprehensive Grammar of the English Language. Longman, Essex.
47. RISSANEN, J. 1989. Stochastic Complexity in Statistical Inquiry. Vol. 15. World Scientific Series in Computer Science, Singapore.
48. SAFFRAN, J. R., NEWPORT, E. L., AND ASLIN, R. N. 1996. Word segmentation: The role of distributional cues. J. Memory Lang. 35, 606-621.
49. SCHONE, P. AND JURAFSKY, D. 2000. Knowledge-free induction of morphology using latent semantic analysis. In Proceedings of the CoNLL-2000 and LLL-2000. 67-72.
50. SCHONE, P. AND JURAFSKY, D. 2001. Knowledge-free induction of inflectional morphologies. In Proceedings of the North American Chapter of the Association for Computational Linguistic Conference.
51. SNOVER, M. G. AND BRENT, M. R. 2001. A Bayesian model for morpheme and paradigm identification. In Proceedings of the 39th Annual Meeting of the ACL. 482-490.
52. SNOVER, M. G., JAROSZ, G. E., AND BRENT, M. R. 2002. Unsupervised learning of morphology using a novel directed search algorithm: Taking the first step. In Proceedings of the Workshop of Morphological & Phonological Learning of ACL. 11-20.
53. WICENTOWSKI, R. 2004. Multilingual noise-robust supervised morphological analysis using the WordFrame model. In Proceedings of the 7th ACL Special Interest Group in Computational Phonology (SIGPHON). Barcelona, Spain. 70-77.
54. YAROWSKY, D., NGAI, G., AND WICENTOWSKI, R. 2001. Inducing multilingual text analysis tools via robust projection across aligned corpora. In Proceedings of the 1st International Conference on Human Language Technology Research (HLT '01). 161-168.
55. YAROWSKY, D. AND WICENTOWSKI, R. 2000. Minimally supervised morphological analysis by multimodal alignment. In Proceedings of the Association for Computational Linguistics (ACL '00). 207-216.
56. YU, H. 2000. Unsupervised word induction using MDL criterion. In Proceedings of the International Symposium of Chinese Spoken Language Processing (ISCSL). Beijing, China.