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Experimental Analysis on Effect of Nasal Tract on Nasalised Vowels

  • Debasish Jyotishi
  • Suman Deb
  • Amit Abhishek
  • Samarendra Dandapat
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 748)

Abstract

In almost every language across the globe nasalised speech is present. Our work is motivated by the fact that nasalised speech detection can improve the speech recognition system. So, to analyse the nasalised speech better, we have designed a device to separate nasal murmur from oral speech, when nasalised speech is spoken. Speech data of different speakers are collected and analysed. Nasalised vowels are analysed first and it has been found that an additional formant is consistently being introduced between 1000 and 1500 Hz. Using various signal processing techniques we analysed different nasalised vowels and found that nasal murmur produced, is invariant irrespective of the nasalised vowels and so is the nasal tract. Nasalisation is being produced in speech by coupling of nasal tract with oral tract. So, when effect of coupling is analysed experimentally, it came out to be addition.

References

  1. 1.
    Glass, J., Zue, V.: Detection of nasalized vowels in American english. In: Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP’85, vol. 10, pp. 1569–1572. IEEE (1985)Google Scholar
  2. 2.
    Vijayalakshmi, P., Ramasubba Reddy, M., O’Shaughnessy, D: Acoustic analysis and detection of hypernasality using a group delay function. IEEE Trans. Biomed. Eng. 54(4), 621–629 (2007)Google Scholar
  3. 3.
    Vijayalakshmi, P., Ramasubba Reddy, M.: Analysis of hypernasality by synthesis. In: INTERSPEECH (2004)Google Scholar
  4. 4.
    Hawkins, S., Stevens, K.N.: Acoustic and perceptual correlates of the non-nasal-nasal distinction for vowels. J. Acoust. Soc. Am. 77(4), 1560–1575 (1985)Google Scholar
  5. 5.
    Rabiner, L.R., Schafer, R.W.: Digital Processing of Speech Signals, vo. 100. Prentice-Hall, Englewood Cliffs (1978)Google Scholar
  6. 6.
    Lim, J.: Spectral root homomorphic deconvolution system. IEEE Trans. Acoust. Speech Signal Process. 27(3), 223–233 (1979)CrossRefGoogle Scholar
  7. 7.
    Murthy, H.A., Yegnanarayana, B.: Formant extraction from group delay function. Speech Commun. 10(3), 209–221 (1991)Google Scholar
  8. 8.
    Yegnanarayana, B.: Formant extraction from linear-prediction phase spectra. J. Acoust. Soc. Am. 63(5), 1638–1640 (1978)CrossRefGoogle Scholar
  9. 9.
    Proakis, J.G., Manolakis, D.G.: Digital Signal Processing, 3rd edn. Prentice-Hall, Englewood Cliffs (1996)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Electronics and Electrical EngineeringIndian Institute of Technology GuwahatiGuwahatiIndia

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