A Method of Speech Signal Analysis Using Multi-level Wavelet Transform
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-15-5400-1_67
Reference22 articles.
1. Tabibian, S., Akbari, A., & Nasersharif, B. (2015). Speech enhancement using a wavelet thresholding method based on symmetric Kullback–Leibler divergence. Signal Processing, 106, 184–197.
2. Lung, S.-Y. (2006). Wavelet feature selection based neural networks with application to the text independent speaker identification. Pattern Recognition, 39(8), 1518–1521.
3. Kotnik, B., & Kačič, Z. (2007). A noise robust feature extraction algorithm using joint wavelet packet subband decomposition and AR modeling of speech signals. Signal Processing, 87(6), 1202–1223.
4. Sahu, P. K., Biswas, A., Bhowmick, A., & Chandra, M. (2014). Auditory ERB like admissible wavelet packet features for TIMIT phoneme recognition. Engineering Science and Technology, an International Journal, 17(3), 145–151.
5. Pavez, E., & Silva, J. F. (2012). Analysis and design of wavelet-packet cepstral coefficients for automatic speech recognition. Speech Communication, 54(6), 814–835.
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