Abstract
This paper addresses the performance enhancement of speech processing applications like speech recognition, speaker identification and language identification in the presence of additive noise with help of proposed adaptive and iterative Wiener filter. This paper deals with the problem of single microphone, frequency domain speech enhancement in noisy environments using Wiener filter in iterative and adaptive manner based on the speech signal statistics (mean and variance). The algorithm achieves good temporal resolution while maintaining formant and harmonic trajectories. The results of implementation of such a structure will demonstrate significant improvements in Oriya isolated word recognition, Oriya continuous digit recognition, speaker identification and language identification performance under noisy conditions. The accuracy of all above applications is increased by 3% to 8% in average due to the proposed speech enhancement technique incorporation in our ongoing research works.
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References
Vaseghi, S.V.: Advanced Digital Signal Processing and Noise Reduction, 3rd edn. Wiley and Sons
Berouti, M., Schwartz, R., Makhoul, J.: Enhancement of speech corrupted by acoustic noise. In: Proc. IEEE Int. Conf. Acoust., Speech Signal Processing, pp. 208–211 (1979)
Boll, S.F.: Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans. Acoust., Speech, Signal Processing ASSP 27, 113–120 (1979)
Ifeachor, E.C.: Digital Signal Processing A Practical Approach, 2nd edn. Pearson Education
Quatieri, T.F.: Discrete-Time Speech Signal Processing Principles and Practice, Third Impression. Pearson Education (2007)
Rabiner, L.R., Schafer, R.W.: Digital Processing of Speech Signals, 1st edn. Pearson Education (2004)
Mohanty, S., Swain, B.K.: Markov Model Based Oriya Isolated Speech Recognizer-An Emerging Solution for Visually Impaired Students in School and Public Examination. Special Issue of IJCCTÂ 2(2,3,4) (2010)
Mohanty, S., Swain, B.K.: Continuous Oriya Digit Recognition using Bakis Model of HMM. International Journal of Computer Information Systems 2(1) (2011)
Mohanty, S., Swain, B.K.: Language Identification using Support Vector Machine, http://desceco.org/O-COCOSDA2010/proceedings/paper_43.pdf
Mohanty, S., Swain, B.K.: Speaker Identification using DTW for Oriya Language. In: International Symposium on Frontier of Research of Speech and Music (FRSM 2009), December 15-16 (2009)
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© 2012 Springer-Verlag Berlin Heidelberg
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Mohanty, S., Swain, B.K. (2012). Adaptive and Iterative Wiener Filter for Oriya Speech Processing Applications. In: Ystad, S., Aramaki, M., Kronland-Martinet, R., Jensen, K., Mohanty, S. (eds) Speech, Sound and Music Processing: Embracing Research in India. CMMR FRSM 2011 2011. Lecture Notes in Computer Science, vol 7172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31980-8_16
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DOI: https://doi.org/10.1007/978-3-642-31980-8_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31979-2
Online ISBN: 978-3-642-31980-8
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