Wavelet-based cepstrum calculation
نویسندگان
چکیده
منابع مشابه
Smooth Cepstrum Calculation Using Modified Bartlett Hanning Window
Cepstrum is an algorithm for analyzing the speech signals in frequency domain. This is conventional method of fundamental peak picking i.e. fundamental frequency or pitch. For a speech signal it is necessary to identify the fundamental frequency correctly in order to have robust system for speaker identification and verification. Using this approach two algorithms has been proposed using Hammin...
متن کاملRecursive Calculation of Mel-Cepstrum from LP Coefficients
The mel-cepstral coefficients are often calculated from the linear prediction coefficients by using recursion formulas. However, the obtained mel-cepstral coefficients have errors caused by truncation in the quefrency domain. The purpose of this report is to point out that the melcepstral coefficients can be calculated from the LP (Linear Prediction) coefficients using the recursion formulas wi...
متن کاملMel-cepstrum-based steganalysis for VoIP steganography
Steganography and steganalysis in VoIP applications are important research topics as speech data is an appropriate cover to hide messages or comprehensive documents. In our paper we introduce a Mel-cepstrum based analysis known from speaker and speech recognition to perform a detection of embedded hidden messages. In particular we combine known and established audio steganalysis features with t...
متن کاملCepstrum Based Voice Transformation Using ANN
The basic goal of the voice conversion system to mimics the characteristics of the target speaker voice by keeping the linguistic and paralinguistic information intact. The characteristics of a speaker in speech reflect at different level such as vocal tract, excitation and prosodic parameters. This propose work based on cepstrum which represents the vocal tract and excitation parameters of the...
متن کاملEffective Value Calculation Using Wavelet Transform
The process of calculating the effective values of voltage and current root mean square (RMS) using Fourier transform (FT) suffers a high computational effort. Since it provides only an amplitude-frequency spectrum, looses time-related information, and is unable to deal with no stationary waveforms, standard definitions are reformulated in the time-frequency domain using the wavelet transform (...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Computational and Applied Mathematics
سال: 2009
ISSN: 0377-0427
DOI: 10.1016/j.cam.2008.03.016