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Effect of Noise on Vowel Onset Point Detection

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Contemporary Computing (IC3 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 168))

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Abstract

This paper discuss the effect of noise on vowel onset point (VOP) detection performance. Noise is one of the major degradation in real-time environments. In this work, initially effect of noise on VOP detection is studied by using recently developed VOP detection method. In this method, VOPs are detected by combining the complementary evidence from excitation source, spectral peaks and modulation spectrum to improve VOP detection performance. Later spectral processing based speech enhancement methods such as spectral subtraction and minimum mean square error (MMSE) are used for preprocessing to improve the VOP detection performance under noise. Performance of the VOP detection is analyzed by using TIMIT database for white and vehicle noise. In general, performance of VOP detection is degraded due to noise and in particular performance is effected significantly due to spurious VOPs introduced at low SNR values. Experimental results indicate that the speech enhancement techniques provides the improvement in the VOP detection performance by eliminating spurious VOPs under noise.

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References

  1. Prasanna, S.R.M., Reddy, B.V.S., Krishnamoorthy, P.: Vowel onset point detection using source, spectral peaks, and modulation spectrum energies. IEEE Transactions on audio, speech, and language processing 17(4), 556–565 (2009)

    Article  Google Scholar 

  2. Prasanna, S.R.M., Suryakanth, V.G., Yegnanarayana, B.: Significance of vowel onset point for speech analysis. In: Signal Processing and Communications (Biennial Conf., IISc), pp. 81–88 (2001)

    Google Scholar 

  3. Suryakanth, V.G., Sekhar, C.C., Yegnanarayana, B.: Detection of vowel onset points in continuous speech using autoassociative neural network models. In: Proc. Int. Conf. Spoken Language Processing, pp. 401–410 (October 2004)

    Google Scholar 

  4. Suryakanth, V.G., Sekhar, C.C., Yegnanarayana, B.: Spotting multilingual consonant-vowel units of speech using neural networks. In: An ISCA Tutorial and Research Workshop on Non-linear Speech Processing, pp. 287–297 (April 2005)

    Google Scholar 

  5. Rao, K.S., Yegnanarayana, B.: Duration modification using glottal closure instants and vowel onset points. Speech Communication 51, 1263–1269 (2009)

    Article  Google Scholar 

  6. Hermes, D.J.: Vowel onset detection. J. Acoust. Soc. Amer. 87, 866–873 (1990)

    Article  Google Scholar 

  7. Wang, J.-H., Chen, S.-H.: A C/V segmentation algorithm for Mandarin speech using wavelet transforms. In: Proc. Int. Conf. Acoust. Speech, Signal Process.,  vol.1, pp. 1261–1264 (September 1999)

    Google Scholar 

  8. Wang, J.-F., Wu, C.-H., Chang, S.-H., Lee, J.-Y.: A hierarchical neural network based on C/V segmentation algorithm for Isolated Mandarin speech recognition. IEEE Trans. Signal Process. 39(9), 2141–2146 (1991)

    Article  Google Scholar 

  9. Suryakanth, V.G., Sekhar, C.C., Yegnanarayana, B.: Extraction of fixed dimension patterns from varying duration segments of consonant-vowel utterances. In: Proc. IEEE ICISIP, pp. 159–164 (2004)

    Google Scholar 

  10. Prasanna, S.R.M., Yegnanarayana, B.: Detection of vowel onset point events using excitation source information. In: Proc. of Interspeech, pp. 1133–1136 (2005)

    Google Scholar 

  11. Boll, S.F.: Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. Acoust., Speech, Signal Process 27, 113–120 (1979)

    Article  Google Scholar 

  12. Ephrain, Y., Malah, D.: Speech enhancement using minimum mean square error short-time spectral amplitude estimator. IEEE Trans. Acoust., Speech, Signal Process 32, 1109–1121 (1984)

    Article  Google Scholar 

  13. Garofolo, J.S.: TIMIT Acoustic-Phonetic Continuous Speech Corpus Linguistic Data Consortium, Philadelphia, PA (1993)

    Google Scholar 

  14. Noisex-92 , http://www.speech.cs.cmu.edu/comp.speech/Section1/Data/noisex.html

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Author information

Authors and Affiliations

  1. G. S. Sanyal School of Telecommunications, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Anil Kumar Vuppala & Saswat Chakrabarti

  2. School of Information Technology, Indian Institute of Technology Kharagpur, Kharagpur, 721302, West Bengal, India

    Jainath Yadav & K. Sreenivasa Rao

Authors
  1. Anil Kumar Vuppala
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  2. Jainath Yadav
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  3. K. Sreenivasa Rao
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  4. Saswat Chakrabarti
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Editor information

Editors and Affiliations

  1. Iowa State University and IIT Bombay, India, 329 Durham, Ames, IA 5001, Iowa, USA

    Srinivas Aluru

  2. Indian Statistical Institute, 203 B.T. Road, 700 108, Kolkata, West Bengal, India

    Sanghamitra Bandyopadhyay

  3. The Ohio State University, 3190 Graves Hall, 333 W 10th Ave, 43210, Columbus, OH, USA

    Umit V. Catalyurek

  4. Department of Computing Science, Chalmers University, Rännvagen 6B, 412 96, Göteborg, Sweden

    Devdatt P. Dubhashi

  5. Dept. of Electrical and Computer Engineering, Iowa State University, 329 Durham, IA 50011, Ames, USA

    Phillip H. Jones

  6. TASSL, Dept. of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Brett Road, NJ 08854-8058, Piscataway, USA

    Manish Parashar

  7. School of Computer Engineering, Nanyang Technological University, N4-02a-32 Nanyang Ave, 639798, Singapore

    Bertil Schmidt

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© 2011 Springer-Verlag Berlin Heidelberg

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Vuppala, A.K., Yadav, J., Rao, K.S., Chakrabarti, S. (2011). Effect of Noise on Vowel Onset Point Detection. In: Aluru, S., et al. Contemporary Computing. IC3 2011. Communications in Computer and Information Science, vol 168. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22606-9_23

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  • DOI: https://doi.org/10.1007/978-3-642-22606-9_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22605-2

  • Online ISBN: 978-3-642-22606-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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