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The Development of an Experimental Discrete Dictation Recognizer

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Informatik-Anwendungen — Trends und Perspektiven

Part of the book series: Informatik-Fachberichte ((INFORMATIK,volume 126))

Abstract

This paper describes an experimental real-time recognizer of isolated word dictation implemented at the IBM Thomas J. Watson Research Center, on a system of commercially available computers and array processors. The recognizer’s intended use is creation of office memoranda. It is based on a 5000-word vocabulary. A specially designed workstation enables the user to correct and edit the transcribed speech.

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References

  1. F. Jelinek, “Continuous speech recognition by statistical methods,” Proc. IEEE, vol. 64, no. 4, pp. 532–556, Apr. 1976.

    Article  Google Scholar 

  2. L. R. Bahl, F. Jelinek, and R. L. Mercer, “A maximum likelihood approach to continuous speech recognition,” IEEE Trans. Pattern Anal. Machine Intell., vol. PAMI-5, no. 2, pp. 179–190, Mar. 1983.

    Article  Google Scholar 

  3. J. D. Gould, J. Conti, and T. Hovanyecz, “Composing letters with a simulated listening typewriter,” Commun. ACM, vol. 26, no. 4, pp. 295–308, Apr. 1983.

    Article  Google Scholar 

  4. E. Goldwasser, an unpublished memorandum, 1980.

    Google Scholar 

  5. J. R. Cohen, “Application of a sensor—Neural model to speech recognition,” to be published.

    Google Scholar 

  6. H. Abut, R. M. Gray, and G. Rebolledo, “Vector quantization of speech and speech-like waveforms,” IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-30, no. 3, pp. 423–435, June 1982.

    Article  Google Scholar 

  7. A. Nadas, R. L. Mercer, L. R. Bahl, R. Bakis, P. S. Cohen, A. G. Cole, F. Jelinek, and B. L. Lewis, “Continuous speech recognition with automatically selected acoustic prototypes obtained by either bootstrapping or clustering,” in Proc. Int. Conf. on Acoustics, Speech, and Signal Processing ( Atlanta, GA, Apr. 1981 ), pp. 1153–1155.

    Google Scholar 

  8. J. D. Ferguson, “Hidden Markov analysis: An introduction,” in J. D. Ferguson, Ed., Hidden Markov Models for Speech. Princeton, NJ: IDA-CRD, Oct. 1980, pp. 8–15.

    Google Scholar 

  9. L. E. Baum, “An inequality and associated maximization technique in statistical estimation of probabilistic functions of Markov processes,” Inequalities, vol. 3, no. 1, pp. 1–8, 1972.

    MathSciNet  Google Scholar 

  10. S. Katz, “Recursive M-Gram language model via a smoothing of Turing’s formula,” a forthcoming paper.

    Google Scholar 

  11. I.J. Good, The Estimation of Probabilities: An Essay on Modem Bayesian Methods. Cambridge, MA: MIT Press, Mar. 1965.

    Google Scholar 

  12. F. Jelinek, “A fast sequential decoding algorithm using a stack,” IBM J. Res. Devel., vol. 13, pp. 675–685, Nov. 1969.

    Article  MathSciNet  MATH  Google Scholar 

  13. D. P. Huttenlocher and V. W. Zue, “A model of lexical access from partial phonetic information,” in Proc. ICAASP84, vol. 2, pp. 26.4.1–26,4. 4, Mar. 1984.

    Google Scholar 

  14. T. Kaneko and N. R. Dixon, “A hierarchical decision approach to large vocabulary discrete utterance recognition,” IEEE Trans. Accoust., Speech, Signal Processing, vol. ASSP-31, no. 5, pp. 1061–1066, Oct. 1983.

    Article  Google Scholar 

  15. A. Averbuch et al., “A real-time, isolated-word, speech recognition system for dictation transcription,” in Proc. Int. Conf. on Acoustics, Speech, and Signal Processing ( Tampa, FL, Mar. 1985 ).

    Google Scholar 

  16. F. Jelinek, R. L. Mercer, L. R. Bahl, and J. K. Baker, “Perplexity —A measure of difficulty of speech recognition tasks,” presented at the 94th Meet. Acoustical Society of America, Miami Beach, FL, Dec. 15, 1977.

    Google Scholar 

  17. M. M. Sondhi and S. E. Levinson, “Computing relative redundancy to measure grammatical constraint in speech recognition tasks,” in Proc. Int. Conf. on Acoustics, Speech, and Signal Processing ( Tulsa, OK, Apr. 1978 ), pp. 409–412.

    Google Scholar 

  18. W. N. Francis and H. Kucera, Frequency Analysis of English Usage. Boston, MA: Houghton-Mifflin, 1982.

    Google Scholar 

  19. J. B. Carroll, P. Davies, and B. Richman, Word Frequency Book. New York, NY: American Heritage, 1971.

    Google Scholar 

  20. H. Kucera, personal communication.

    Google Scholar 

  21. R. L. Mercer, personal communication.

    Google Scholar 

  22. F. Jelinek, Probabilistic Information Theory. New York, NY: McGraw-Hill, 1968.

    MATH  Google Scholar 

  23. C. E. Shannon, “Prediction and entropy of printed English,” Bell Syst. Tech. J., vol. 30, pp. 50–64, 1951.

    MATH  Google Scholar 

  24. T. M. Cover and R. C. King, “A convergent gambling estimate of the entropy of English,” IEEE Trans. Informat. Theory, vol. IT-24, no. 4, pp. 413–420, July 1978.

    Article  MathSciNet  Google Scholar 

  25. S. Delia Pietra and V. Delia Pietra, personal communication.

    Google Scholar 

  26. J. D. Gould and S. J. Boies, “Human factors challenges in creating a principal support office system—The speech filing system approach,” ACM Trans. Office Inform. Syst., vol. 1, no. 4, pp. 273–298, Oct. 1983.

    Google Scholar 

  27. 27], “Writing, dictating, and speaking letters,” Science, vol. 201, pp. 1145–1147, 1978.

    Article  Google Scholar 

  28. L. R. Bahl and F. Jelinek, “Decoding for channels with insertions, deletions, and substitutions with applications to speech recognition,” IEEE Trans. Informat. Theory, vol. IT-21, no. 4, pp. 404–411, July 1975,

    Google Scholar 

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© 1986 Springer-Verlag Berlin Heidelberg

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Jelinek, F. (1986). The Development of an Experimental Discrete Dictation Recognizer. In: Hommel, G., Schindler, S. (eds) Informatik-Anwendungen — Trends und Perspektiven. Informatik-Fachberichte, vol 126. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-71388-0_9

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  • DOI: https://doi.org/10.1007/978-3-642-71388-0_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-16813-3

  • Online ISBN: 978-3-642-71388-0

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