Aligning text and phonemes for speech technology applications using an EM-like algorithm

International Journal of Speech Technology

Volumn 8, Issue 2, 2005, Pages 147-160

  Damper, R I ^a   Marchand, Y ^b   Marsters, J D S ^a   Bazin, A I ^a  

^a UNIVERSITY OF SOUTHAMPTON   (United Kingdom)

^b NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

Dynamic programming; EM algorithm; Pronunciation by analogy; String alignment; Text to speech synthesis

Indexed keywords

ALGORITHMS; DATA REDUCTION; DYNAMIC PROGRAMMING; SPEECH PROCESSING; SPEECH SYNTHESIS; WORD PROCESSING;

EM ALGORITHM; PRONUNCIATION BY ANALOGY; STRING ALIGNMENT; TEXT-TO-SPEECH SYNTHESIS;

SPEECH ANALYSIS;

EID: 30344444313     PISSN: 13812416     EISSN: 15728110     Source Type: Journal    
DOI: 10.1007/s10772-005-2166-6     Document Type: Conference Paper

References (54)

1. Abercrombie, D. (1981). Extending the Roman alphabet: Some orthographic experiments of the past four centuries. In R.E. Asher and E. Henderson (Eds.), Towards a History of Phonetics. Edinburgh, UK: Edinburgh University Press, pp. 207-224.
2. Bagshaw, P.C. (1998). Phonemic transcription by analogy in text-to-speech synthesis: Novel word pronunciation and lexicon compression. Computer Speech and Language, 12(2):119-142.
3. Baum, L.E. (1972). An inequality and associated maximization technique in statistical estimation for probabilistic functions of Markov processes. In Inequalities III: Proceedings of the Third Symposium on Inequalities, Los Angeles, CA, pp. 1-8.
4. Bellman, R. (1957). Dynamic Programming. Princeton, NJ: Princeton University Press.
5. Black, A.W., Lenzo, K., and Pagel, V. (1998). Issues in building general letter-to-sound rules. In Proceedings of 3rd European Speech Communication Association (ESCA)/COCOSDA International Workshop on Speech Synthesis. Jenolan Caves, Australia, pp. 77-80.
6. Carney, E. (1994). A Survey of English Spelling. London, UK: Routledge.
7. Chomsky, N. and Halle, M. (1968). The Sound Pattern of English. New York, NY: Harper and Row.
8. Coltheart, M. (1978). Lexical access in simple reading tasks. In G. Underwood (Ed.), Strategies of Information Processing. New York: Academic Press, pp. 151-216.
9. Coltheart, M. (1984). Writing systems and reading disorders. In L. Henderson (Ed.), Orthographies and Reading: Perspectives from Cognitive Psychology, Neuropsychology and Linguistics. London, UK: Lawrence Erlbaum Associates, pp. 67-79.
10. Damper, R.I. (Ed.) (2001). Data-Driven Methods in Speech Synthesis. Dordrecht, The Netherlands: Kluwer Academic Publishers.
11. Damper, R.I. and Eastmond, J.F.G. (1996). Pronouncing text by analogy. In Proceedings of 16th International Conference on Computational Linguistics. Copenhagen, Denmark, Vol 2, pp. 268-273.
12. Damper, R.I. and Eastmond, J.F.G. (1997). Pronunciation by analogy: Impact of implementational choices on performance. Language and Speech, 40(1):1-23.
13. Damper, R.I., Marchand, Y., Adamson, M.J., and Gustafson, K. (1999). Evaluating the pronunciation component of text-to-speech systems for English: A performance comparison of different approaches. Computer Speech and Language, 13(2):155-176.
14. Dedina, M.J. and Nusbaum, H.C. (1991). PRONOUNCE: A program for pronunciation by analogy. Computer Speech and Language, 5(1):55-64.
15. Dempster, A.P., Laird, N.M., and Rubin, D.B. (1977). Maximum-likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, Series B, 39(1):1-38.
16. Federici, S., Pirrelli, V., and Yvon, F. (1995). Advances in analogy-based learning: False friends and exceptional items in pronunciation by paradigm-driven analogy. In Proceedings of International Joint Conference on Artificial Intelligence (IJCAI'95) Workshop on New Approaches to Learning for Natural Language Processing, Montreal, Canada, pp. 158-163.
17. Forney, G. D. (1973). The Viterbi algorithm. In Proceedings of the IEEE, vol. 61, no. 3, pp. 268-278.
18. Hartley, H. (1958). Maximum likelihood estimation from incomplete data. Biometrics 14, 174-194.
19. Henderson, L. (1984). Writing systems and reading processes. In L. Henderson (Ed.), Orthographies and Reading: Perspectives from Cognitive Psychology, Neuropsychology and Linguistics. London, UK: Lawrence Erlbaum Associates, pp. 11-24.
20. Hopcroft, J.E., Motwani, R., and Ullman, J.D. (2001). Introduction to Automata Theory, Languages, and Computation, 2nd ed. Boston, MA: Addison-Wesley.
21. Jansche, M. (2001). Re-engineering letter to sound rules. In Second Meeting of the North American Chapter of the Association for Computational Linguistics, NAACL 2001, Pittsburg, PA. Paper N01-1015 in on-line archive at http://acl.ldc.upenn.edu/N/N01/.
22. Katz, L. and Feldman, L.B. (1981). Linguistic coding in word recognition: comparisons between a deep and a shallow orthography. In A.M. Lesgold and C.A. Perfetti (Eds.), Interactive Processes in Reading. Hillsdale, NJ: Lawrence Erlbaum Associates, pp. 85-106.
23. Knill, K. and Young, S. (1997). Hidden Markov models in speech and language processing. See Young and Bloothooft (1997), pp. 27-68.
24. Kruskal, J.B. (1983). An overview of sequence comparison. In D. Sankoff and J. B. Kruskal (Eds.), Time Warps, String Edits and Macromolecules: The Theory and Practice of Sequence Comparison. Reading, MA: Addison-Wesley, pp. 11-44.
25. Lawrence, S.G.C. and Kaye, G. (1986). Alignment of phonemes with their corresponding orthography. Computer Speech and Language, 1(2):153-165.
26. Liberman, I., Liberman, A., Mattingly, I. and Shankweiler, D. (1980). Orthography and the beginning reader. In J. Kavanagh and R. Venezky (Eds.), Orthography, Reading and Dyslexia. Baltimore, OH: University Park Press, pp. 137-153.
27. Luk, R.W.P. and Damper, R.I. (1991). A novel approach to inferring letter-phoneme correspondences. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'91. Toronto, Canada, Vol 2, pp. 741-744.
28. Luk, R.W.P. and Damper, R.I. (1992). Inference of letter-phoneme correspondences by delimiting and dynamic time warping techniques. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'92. San Francisco, CA, Vol 2, pp. II.61-II.64.
29. Luk, R.W.P. and Damper, R.I. (1993). Inference of letter-phoneme correspondences with pre-defined consonant and vowel patterns. In Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP'93. Minneapolis, MN, Vol 2, pp. II.203-II.206.
30. Luk, R.W.P. and Damper, R.I. (1996). Stochastic phonographic transduction for English. Computer Speech and Language, 10(2):133-153.
31. Luk, R.W.P. and Damper, R.I. (1998). Computational complexity of a fast Viterbi decoding algorithm for stochastic letter-phoneme transduction. IEEE Transactions on Speech and Audio Processing, 6(3):217-225.
32. Marchand, Y. and Damper, R.I. (2000). A multistrategy approach to improving pronunciation by analogy. Computational Linguistics, 26(2):195-219.
33. McCulloch, N., Bedworth, M., and Bridle, J. (1987). NETspeak - a re-implementation of NETtalk. Computer Speech and Language, 2(3/4):289-301.
34. McLachlan, G.J. and Krishnan, T. (1997). The EM Algorithm and Extensions. New York, NY: John Wiley.
35. Moon, T.K. (1996). The expectation-maximization algorithm. IEEE Signal Processing Magazine, 13(6):47-60.
36. Needleman, S.B. and Wunsch, C.D. (1970). An efficient method applicable to the search for similarities in the amino acid sequences of two proteins. Journal of Molecular Biology, 48(3):444-453.
37. Neuhoff, D.L. (1975). The Viterbi algorithm as an aid in text recognition. In IEEE Transactions on Information Theory, IT-21:222-226.
38. Parfitt, S.H. and Sharman, R.A. (1991). A bidirectional model of English pronunciation. In Proceedings of 2nd European Conference on Speech Communication and Technology, Eurospeech'91. Genova, Italy, Vol 2, pp. 800-804.
39. Pirrelli, V. and Federici, S. (1994). On the pronunciation of unknown words by analogy in text-to-speech systems. In Proceedings of the Second Onomastica Research Colloquium. London, UK, pp. 43-50.
40. Pirrelli, V. and Federici, S. (1995). You'd better say nothing than something wrong: Analogy, accuracy and text-to-speech applications. In Proceedings of 4th European Conference on Speech Communication and Technology, Eurospeech'95. Madrid, Spain, Vol 1, pp. 855-858.
41. Pirrelli, V. and Yvon, F. (1999). The hidden dimension: A paradigmatic view of data-driven NLP. Journal of Experimental and Theoretical Artificial Intelligence, 11(3):391-408.
42. Ristad, E.S. and Yianilos, P.M. (1998). Learning string-edit distance. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(5):522-532.
43. Sampson, G. (1985). Writing Systems. London, UK: Hutchinson.
44. Sejnowski, T.J. and Rosenberg, C.R. (1987). Parallel networks that learn to pronounce English text. Complex Systems, 1(1):145-168.
45. Sullivan, K.P.H. (2001). Analogy, the corpus and pronunciation. See Damper (2001), pp. 45-70.
46. Sullivan, K.P.H. and Damper, R.I. (1993). Novel-word pronunciation: A cross-language study. Speech Communication, 13(3-4):441-452.
47. Turvey, M.T., Feldman, L.B. and Lukatela, G. (1984). The Serbo-Croatian orthography constrains the reader to a phonologically analytic strategy. In L. Henderson (Ed.) Orthographies and Reading: Perspectives from Cognitive Psychology, Neuropsychology and Linguistics. London, UK: Lawrence Erlbaum Associates, pp. 81-89.
48. Venezky, R.L. (1965). A Study of English Spelling-to-Sound Correspondences on Historical Principles. Ann Arbor, MI: Ann Arbor Press.
49. Venezky, R.L. (1970). The Structure of English Orthography. The Hague, The Netherlands: Mouton.
50. Viterbi, A.J. (1967). Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory, IT-13(2):260-269.
51. Wu, C.F.J. (1983). On the convergence properties of the EM algorithm. Annals of Statistics, 11(1):95-103.
52. Young, S. and G. Bloothooft (Eds.) (1997). Corpus-Based Methods in Language and Speech Processing. Dordrecht, The Netherlands: Kluwer Academic Publishers.
53. Yvon, F. (1996a). Grapheme-to-phoneme conversion using multiple unbounded overlapping chunks. In Proceedings of Conference on New Methods in Natural Language Processing (NeMLaP-2'96). Ankara, Turkey, pp. 218-228.
54. Yvon, F. (1996b). Prononcer par Analogie: Motivations, Formalisations et Évaluations. PhD thesis, ENST, Paris, France.