Normalized Wavelet Hybrid Feature for Consonant Classification in Noisy Environments
This paper investigates on the use of Wavelet Transform (WT) to model and recognize the utterances of Consonant – Vowel (CV) speech units in noisy environments. The peculiarity of the proposed method lies in the fact that using WT, non stationary nature of the speech signal can be accurately considered. A hybrid feature extraction namely Normalized Wavelet Hybrid Feature (NWHF) using the combination of Classical Wavelet Decomposition (CWD) and Wavelet Packet Decomposition (WPD) along with z-score normalization technique are studied here. CV speech unit recognition tasks performed for noisy speech units using Artificial Neural Network (ANN) and k – Nearest Neighborhood (k – NN) are also presented. The result indicates the robustness of the proposed technique based on WT in additive noisy condition.
KeywordsSpeech Signal Wavelet Transform Recognition Accuracy Automatic Speech Recognition Noisy Environment
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- 1.Gold, B., Morgan, N.: Speech and Audio Signal Processing. John Wiley & Sons Inc., New York (2000)Google Scholar
- 2.Ramachandran, H.P.: Encyclopedia of Language and Linguistics. Pergamon Press, OxfordGoogle Scholar
- 3.Bourlard, H., Dupont, S.: Subband-based speech recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP Signal Processing (ICASSP 1997), Munich, Germany, vol. 2, pp. 1251–1254 (April 1997)Google Scholar
- 4.Gupta, M., Gilbert, A.: Robust speech recognition using wavelet coefficient features. In: IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU 2001), Madonna di Campiglio, Trento, Italy, pp. 445–448 (December 2001)Google Scholar
- 5.Sarikaya, R., Pellom, B.L., Hansen, J.H.L.: Wavelet packet transform features with application to speaker Identification. In: 3rd IEEE Nordic Signal Processing Symposium (NORSIG 1998), Vigsø, Denmark, pp. 81–84 (June 1998)Google Scholar
- 8.Soman, K.P., Ramachandran, K.I.: Insight into Wavelets, from Theory to Practice. Prentice Hall of India (2005)Google Scholar