Title :
A sinusoidal audio and speech analysis/synthesis model based on improved EMD by adding pure tone
Author :
Li, Xiao-ming ; Bao, Chang-chun ; Jia, Mao-shen
Author_Institution :
Speech & Audio Signal Process. Lab., Beijing Univ. of Technol., Beijing, China
Abstract :
A multi-resolution speech and audio sinusoidal analysis/synthesis model based on an improved Empirical Mode Decomposition (EMD) is proposed in this paper. Because of the special filtering characteristic and superiority in dealing with non-stationary signal of EMD, a preprocessing module is adopted to classify the original signal by using the energy ratio and spectrum center of each Intrinsic Mode Function (IMF). A pure tone is added into original signal to extract the noise-like high frequency components without destroying the harmonics of signal. Then a multi-resolution Perceptual Weighted Matching Pursuit (PWMP) and frequency fine search method are adopted to estimate the sinusoidal parameters. Finally, objective measurements of perceived audio quality (PEAQ) show that this model can be effective for the audio synthesis.
Keywords :
audio signal processing; filtering theory; iterative methods; speech processing; speech synthesis; EMD; IMF; PEAQ; PWMP; audio sinusoidal analysis; audio sinusoidal synthesis; empirical mode decomposition; energy ratio; frequency fine search method; intrinsic mode function; multiresolution perceptual weighted matching pursuit; multiresolution speech analysis; perceived audio quality; pure tone; spectrum center; speech synthesis; Adaptation models; Analytical models; Educational institutions; Encoding; Noise; Psychoacoustic models; Speech; audio analysis and synthesis; empirical mode decomposition; sinusoidal model;
Conference_Titel :
Machine Learning for Signal Processing (MLSP), 2011 IEEE International Workshop on
Conference_Location :
Santander
Print_ISBN :
978-1-4577-1621-8
Electronic_ISBN :
1551-2541
DOI :
10.1109/MLSP.2011.6064614