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Performance of Speaker Independent Language Identification System Under Various Noise Environments

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 433))

Abstract

Language Identification has gained significant importance in recent years, both in research and commercial market place, demanding an improvement in the ability of machines to distinguish languages. Although methods like Gaussian Mixture Models, Hidden Markov Models and Neural Networks are used for identifying languages the problem of language identification in noisy environments could not be addressed so far. This paper addresses the capability of an Automatic Language Identification (LID) system in clean and noisy environments. The language identification studies are performed using IITKGP-MLILSC (IIT Kharagpur-Multilingual Indian Language Speech Corpus) databases which consists of 27 languages.

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References

  1. K. Sreenivasa Rao, Sudhamay Maity, and V. Ramu Reddy. “Pitch synchronous and glottal closure based speech analysis for language recognition.”International Journal of Speech Technology 16.4 (2013): 413–430.

    Google Scholar 

  2. Reynolds, Douglas A., and Richard C. Rose. “Robust text-independent speaker identification using Gaussian mixture speaker models.” Speech and Audio Processing, IEEE Transactions on 3.1 (1995): 72–83.

    Google Scholar 

  3. Zissman, Marc A. “Comparison of four approaches to automatic language identification of telephone speech.” IEEE Transactions on Speech and Audio Processing 4.1 (1996): 31.

    Google Scholar 

  4. Foil, Jerry. “Language Identification Using Noisy Speech.” Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP’86.. Vol. 11. IEEE, 1986.

    Google Scholar 

  5. Goodman, Fred J., Alvin F. Martin, and R. Wohlford. “Improved automatic language identification in noisy speech.” Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on. IEEE, 1989.

    Google Scholar 

  6. Hegde, Rajesh M., and Hema A. Murthy. “Automatic language identification and discrimination using the modified group delay feature.” Intelligent Sensing and Information Processing, 2005. Proceedings of 2005 International Conference on. IEEE, 2005.

    Google Scholar 

  7. Ambikairajah, E., Li, H., Wang, L., Yin, B., & Sethu, V. (2011). Language identification: a tutorial. Circuits and Systems Magazine, IEEE, 11(2), 82–108.

    Google Scholar 

  8. Dempster, Arthur P., Nan M. Laird, and Donald B. Rubin. “Maximum likelihood from incomplete data via the EM algorithm.” Journal of the Royal Statistical Society. Series B (Methodological) (1977): 1–38.

    Google Scholar 

  9. Mary, Leena, and Bayya Yegnanarayana. “Extraction and representation of prosodic features for language and speaker recognition.” Speech communication 50.10 (2008): 782–796.

    Google Scholar 

  10. Jothilakshmi, S., Vennila Ramalingam, and S. Palanivel. “A hierarchical language identification system for Indian languages.” Digital Signal Processing 22.3 (2012): 544–553.

    Google Scholar 

  11. Maity, Sudhamay, Anil Kumar Vuppala, K. Sreenivasa Rao, and Dipanjan Nandi. “IITKGP-MLILSC speech database for language identification.” In Communications (NCC), 2012 National Conference on, pp. 1–5. IEEE, 2012.

    Google Scholar 

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Acknowledgments

The authors are grateful to Dr K Sreenivasa Rao, Associate Professor and his team at School of Information Technology (SIT), IIT Kharagpur for providing IIT Kharagpur-Multilingual Indian Language Speech Corpus) databases which consists of 27 languages. We would also like to thank their anonymous suggestions and helpful discussions.

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Correspondence to Phani Kumar Polasi .

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© 2016 Springer India

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Polasi, P.K., Sri Rama Krishna, K. (2016). Performance of Speaker Independent Language Identification System Under Various Noise Environments. In: Satapathy, S., Mandal, J., Udgata, S., Bhateja, V. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 433. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2755-7_33

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  • DOI: https://doi.org/10.1007/978-81-322-2755-7_33

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2753-3

  • Online ISBN: 978-81-322-2755-7

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