Skip to main content
SpringerLink
Log in

SCA: Phonetic Alignment Based on Sound Classes

  • Conference paper
New Directions in Logic, Language and Computation (ESSLLI 2010, ESSLLI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7415))

Abstract

In this paper I present the most recent version of the SCA method for pairwise and multiple alignment analyses. In contrast to previously proposed alignment methods, SCA is based on a novel framework of sequence alignment which combines new approaches to sequence modeling in historical linguistics with recent developments in computational biology. In contrast to earlier versions of SCA [1,2] the new version comes along with a couple of modifications that significantly improve the performance and the application range of the algorithm: A new sound class model was defined which works well on highly divergent sequences, the algorithm for pairwise alignment was modified to be sensitive to secondary sequence structures such as syllable boundaries, and an algorithm for the pre-processing of the data in multiple alignment analyses [3] was included to cope for the bias resulting from progressive alignment analyses. In order to test the method, a new gold standard for pairwise and multiple alignment analyses was created which consists of 45 947 sequences covering a total of 435 different taxa belonging to six different language families.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. List, J.M.: Phonetic alignment based on sound classes. In: Slavkovik, M. (ed.) Proceedings of the 15th Student Session of the European Summer School for Logic, Language and Information, Kopenhagen, pp. 192–202 (2010)

    Google Scholar 

  2. List, J.M.: Multiple sequence alignment in historical linguistics. A sound class based approach. In: Proceedings of ConSOLE XIX (2011) (forthcoming)

    Google Scholar 

  3. Notredame, C., Higgins, D.G., Heringa, J.: T-Coffee. A novel method for fast and accurate multiple sequence alignment. Journal of Molecular Biology 302, 205–217 (2000)

    Article  Google Scholar 

  4. Gray, R.D., Atkinson, Q.D.: Language-tree divergence times support the Anatolian theory of Indo-European origin. Nature 426(6965), 435–439 (2003)

    Article  Google Scholar 

  5. Holman, E.W., Brown, C.H., Wichmann, S., Müller, A., Velupillai, V., Hammarström, H., Sauppe, S., Jung, H., Bakker, D., Brown, P., Belyaev, O., Urban, M., Mailhammer, R., List, J.M., Egorov, D.: Automated dating of the world’s language families based on lexical similarity. Current Anthropology 52(6), 841–875 (2011)

    Article  Google Scholar 

  6. Baxter, W.H., Manaster Ramer, A.: Beyond lumping and splitting. Probabilistic issues in historical linguistics. In: Renfrew, C., McMahon, A., Trask, L. (eds.) Time Depth in Historical Linguistics, pp. 167–188. McDonald Institute for Archaeological Research, Cambridge (2000)

    Google Scholar 

  7. Kessler, B.: The significance of word lists. Statistical tests for investigating historical connections between languages. CSLI Publications, Stanford (2001)

    Google Scholar 

  8. Kondrak, G.: Algorithms for language reconstruction. Dissertation. University of Toronto, Toronto (2002)

    Google Scholar 

  9. Prokić, J., Wieling, M., Nerbonne, J.: Multiple sequence alignments in linguistics. In: Proceedings of the EACL 2009 Workshop on Language Technology and Resources for Cultural Heritage, Social Sciences, Humanities, and Education, pp. 18–25. Association for Computational Linguistics, Stroudsburg (2009)

    Chapter  Google Scholar 

  10. Turchin, P., Peiros, I., Gell-Mann, M.: Analyzing genetic connections between languages by matching consonant classes. Journal of Language Relationship 3, 117–126 (2010)

    Google Scholar 

  11. Covington, M.A.: An algorithm to align words for historical comparison. Computational Linguistics 22(4), 481–496 (1996)

    Google Scholar 

  12. Ross, M., Durie, M.: Introduction. In: Durie, M. (ed.) The Comparative Method Reviewed. Regularity and Irregularity in Language Change, pp. 3–38. Oxford University Press, New York (1996)

    Google Scholar 

  13. Trask, R.L. (ed.): The dictionary of historical and comparative linguistics. Edinburgh University Press, Edinburgh (2000)

    Google Scholar 

  14. Lass, R.: Historical linguistics and language change. Cambridge University Press, Cambridge (1997)

    Book  Google Scholar 

  15. Gusfield, D.: Algorithms on strings, trees and sequences. Cambridge University Press, Cambridge (1997)

    Book  MATH  Google Scholar 

  16. Needleman, S.B., Wunsch, C.D.: A gene method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology 48, 443–453 (1970)

    Article  Google Scholar 

  17. Wagner, R.A., Fischer, M.J.: The string-to-string correction problem. Journal of the Association for Computing Machinery 21(1), 168–173 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  18. Eddy, S.R.: Where did the BLOSUM62 alignment score matrix come from? Nature Biotechnology 22(8), 1035–1036 (2004)

    Article  Google Scholar 

  19. Rosenberg, M.S.: Sequence alignment. Concepts and history. In: Rosenberg, M.S. (ed.) Sequence Alignment. Methods, Models, Concepts, and Strategies, pp. 1–22. University of California Press, Berkeley and Los Angeles and London (2009)

    Google Scholar 

  20. Durbin, R., Eddy, S.R., Krogh, A., Mitchinson, G.: Biological sequence analysis. Probabilistic models of proteins and nucleic acids, 7th edn. Cambridge University Press, Cambridge (2002)

    Google Scholar 

  21. Smith, T.F., Waterman, M.S.: Identification of common molecular subsequences. Journal of Molecular Biology 1, 195–197 (1981)

    Article  Google Scholar 

  22. Morgenstern, B., Dress, A., Werner, T.D.: Multiple DNA and protein sequence alignment based on segment-to-segment comparison. Proceedings of the National Acadamy of Science, USA 93, 12098–12103 (1996)

    Article  MATH  Google Scholar 

  23. Henikoff, S., Henikoff, J.G.: Amino acid substitution matrices from protein blocks. PNAS 89(22), 10915–10919 (1992)

    Article  Google Scholar 

  24. Sokal, R.R., Michener, C.D.: A statistical method for evaluating systematic relationships. University of Kansas Scientific Bulletin 28, 1409–1438 (1958)

    Google Scholar 

  25. Saitou, N., Nei, M.: The neighbor-joining method: A new method for reconstructing phylogenetic trees. Molecular Biology and Evolution 4(4), 406–425 (1987)

    Google Scholar 

  26. Feng, D.F., Doolittle, R.F.: Progressive sequence alignment as a prerequisite to correct phylogenetic trees. Journal of Molecular Evolution 25(4), 351–360 (1987)

    Article  Google Scholar 

  27. Dolgopolsky, A.B.: Gipoteza drevnejšego rodstva jazykovych semej Severnoj Evrazii s verojatnostej točky zrenija (A probabilistic hypothesis concerning the oldest relationships among the language families of Northern Eurasia). Voprosy Jazykoznanija 2, 53–63 (1964)

    Google Scholar 

  28. Dolgopolsky, A.B.: A probabilistic hypothesis concerning the oldest relationships among the language families of northern Eurasia. In: Shevoroshkin, V.V. (ed.) Typology, Relationship and Time, pp. 27–50. Karoma Publisher, Ann Arbor (1986)

    Google Scholar 

  29. Brown, C.H., Holman, E.W., Wichmann, S.: Sound correspondences in the world’s languages (2011), Online manuscript, PDF, http://wwwstaff.eva.mpg.de/~wichmann/wwcPaper23.pdf

  30. Brown, C.H., Holman, E.W., Wichmann, S., Velupillai, V., Cysouw, M.: Automated classification of the world’s languages. Sprachtypologie und Universalienforschung 61(4), 285–308 (2008)

    Google Scholar 

  31. Thompson, J.D., Higgins, D.G., Gibson, T.J.: CLUSTAL W. Nucleic Acids Research 22(22), 4673–4680 (1994)

    Article  Google Scholar 

  32. Geisler, H.: Akzent und Lautwandel in der Romania. Narr, Tübingen (1992)

    Google Scholar 

  33. Hóu, J. (ed.): Xiàndài Hànyǔ fāngyán yīnkù (Phonological database of Chinese dialects). Shànghǎi Jiàoyǔ, Shanghai (2004)

    Google Scholar 

  34. Downey, S.S., Hallmark, B., Cox, M.P., Norquest, P., Lansing, S.: Computational feature-sensitive reconstruction of language relationships: Developing the ALINE distance for comparative historical linguistic reconstruction. Journal of Quantitative Linguistics 15(4), 340–369 (2008)

    Article  Google Scholar 

  35. Wang, F.: Comparison of languages in contact. Institute of Linguistics Academia Sinica, Taipei (2006)

    Google Scholar 

  36. Thompson, J.D., Plewniak, F., Poch, O.: A comprehensive comparison of multiple sequence alignment programs. Nucleic Acids Research 27(13), 2682–2690 (1999)

    Article  Google Scholar 

  37. Raghava, G.P.S., Barton, G.J.: Quantification of the variation in percentage identity for protein sequence alignments. BMC Bioinformatics 7(415) (2006)

    Google Scholar 

  38. Heggarty, P.: Sounds of the Andean languages. Online resource, http://www.quechua.org.uk/

  39. Allen, B.: Bai Dialect Survey. SIL International (2007)

    Google Scholar 

  40. Almberg, J., Skarbø, K.: Nordavinden og sola. En norsk dialektprøvedatabase på nettet (The North Wind and the Sun. A Norwegian dialect database on the web) (2011), Online resource, http://www.ling.hf.ntnu.no/nos/

  41. Gauchat, L., Jeanjaquet, J., Tappolet, E.: Tableaux phonétiques des patois suisses romands. Attinger, Neuchâtel (1925)

    Google Scholar 

  42. Renfrew, C., Heggarty, P.: Languages and origins in europe. Online resource, http://www.languagesandpeoples.com/

Download references

Author information

Authors and Affiliations

  1. Heinrich Heine University Düsseldorf, Germany

    Johann-Mattis List

Authors
  1. Johann-Mattis List
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Psychology, Stanford University, 420 Jordan Hall, 450 Serra Mall, 94305, Stanford, CA, USA

    Daniel Lassiter

  2. University of Luxembourg, 6, Rue Richard Coudenhove Kalergi, 1359, Luxembourg

    Marija Slavkovik

1 Electronic Supplementary Material

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

List, JM. (2012). SCA: Phonetic Alignment Based on Sound Classes. In: Lassiter, D., Slavkovik, M. (eds) New Directions in Logic, Language and Computation. ESSLLI ESSLLI 2010 2011. Lecture Notes in Computer Science, vol 7415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31467-4_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-31467-4_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31466-7

  • Online ISBN: 978-3-642-31467-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation