Time-frequency analysis to detect signature in signals
Priyadharshini Prabhakaran, M. Renuga, M. Banu Sundareswari
Abstract
Priyadharshini Prabhakaran, M. Renuga, M. Banu Sundareswari
Abstract
This paper describes the pitch detection techniques using autocorrelation method and modified autocorrelation method involving preprocessing and extraction of pitch pattern. The autocorrelation method and Time-Frequency analysis namely spectrogram has been used to detect the fundamental frequency (or) pitch of the signal, energy and envelope detection for different speech patterns. Speech based systems have many advantages including ease of use and implementation, low cost and high user acceptance. Simulation are done by MATLAB/SIMULINK.
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This paper describes the pitch detection techniques using autocorrelation method and modified autocorrelation method involving preprocessing and extraction of pitch pattern. The autocorrelation method and Time-Frequency analysis namely spectrogram has been used to detect the fundamental frequency (or) pitch of the signal, energy and envelope detection for different speech patterns. Speech based systems have many advantages including ease of use and implementation, low cost and high user acceptance. Simulation are done by MATLAB/SIMULINK.
Key concepts: Autocorrelation, Spectrogram, Pitch detection algorithm, Computer science, Preprocessor, Speech recognition, Signature (topology), Autocorrelation technique