TY - GEN
T1 - Kadin/Erkek Ötümlü Ses Kalintilarinin 1/f Özelliǧinin İncelenmesi
AU - Baykut, Süleyman
AU - Akgül, Tayfun
PY - 2004
Y1 - 2004
N2 - In this paper, we examine the 1/f nature of voiced speech residual signal. Speech signals are generally classified as voiced or unvoiced. Voiced speech signals are considered to be generated by the vocal cords vibration signal exciting the vocal tract. In our model, the vocal tract is considered as a linear system. The excitation signal is the 1/f noise which is called the speech residual signal. Since the vowels are the largest and the most evident voiced phoneme group, we study some of these vowels, i.e., /IY/, /IH/, /EI/, /EH/, /AE/, /ER/, /AH/, /AW/, /OA/, /OO/, /UW/ and /UH/ which are generated by several men and women. To extract the speech residual, first, we force to whiten the power spectrum of the speech signal by using a pre-emphasize filter and then perform the linear predictive analysis on the whitened speech to obtain the vocal tract parameters. The speech residual signal is obtained by the inverse filter. A wavelet decomposition technique is applied to the residual signal to obtain the wavelet coefficients. The power-law relationship is observed in the progression of the variances of these coefficients along scales. The self-similarity parameters (the slope of the progression) are then estimated. We investigate and compare the behavior of the self-similarity parameters for the speeches of 40 men and women.
AB - In this paper, we examine the 1/f nature of voiced speech residual signal. Speech signals are generally classified as voiced or unvoiced. Voiced speech signals are considered to be generated by the vocal cords vibration signal exciting the vocal tract. In our model, the vocal tract is considered as a linear system. The excitation signal is the 1/f noise which is called the speech residual signal. Since the vowels are the largest and the most evident voiced phoneme group, we study some of these vowels, i.e., /IY/, /IH/, /EI/, /EH/, /AE/, /ER/, /AH/, /AW/, /OA/, /OO/, /UW/ and /UH/ which are generated by several men and women. To extract the speech residual, first, we force to whiten the power spectrum of the speech signal by using a pre-emphasize filter and then perform the linear predictive analysis on the whitened speech to obtain the vocal tract parameters. The speech residual signal is obtained by the inverse filter. A wavelet decomposition technique is applied to the residual signal to obtain the wavelet coefficients. The power-law relationship is observed in the progression of the variances of these coefficients along scales. The self-similarity parameters (the slope of the progression) are then estimated. We investigate and compare the behavior of the self-similarity parameters for the speeches of 40 men and women.
UR - http://www.scopus.com/inward/record.url?scp=18844391289&partnerID=8YFLogxK
M3 - Konferans katkısı
AN - SCOPUS:18844391289
SN - 0780383184
SN - 9780780383180
T3 - Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004
SP - 216
EP - 219
BT - Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004
A2 - Gunsel, B.
T2 - Proceedings of the IEEE 12th Signal Processing and Communications Applications Conference, SIU 2004
Y2 - 28 April 2004 through 30 April 2004
ER -