Features of Wavelet Packet Decomposition and Discrete Wavelet Transform for Malayalam Speech Recognition
نویسنده
چکیده
This paper explains a study conducted based on wavelet based transform techniques. We have used discrete wavelet transform and wavelet packet decomposition. The database is created by using Malayalam (one of the south Indian Languages) language spoken words. Daubechies type of mother wavelet was used for the experiment. Six hundred and forty samples are collected, for the experiment. The feature vector was produced for all words and formed a training set for classification and recognition purpose. A sequence of wavelet decomposition levels were carried out to achieve a good feature vector. Feature vectors of element size twelve and eight were collected for all the words by using discrete wavelet transform and wavelet packet decomposition techniques respectively. Results are also prepared for the comparison of the signal at each decomposition level. The physical changes that are occurred during each decomposition levels could be observed from the results.
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