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Unformatted text preview: per Resolution determinator (eSRFD) based on the SRFD method which uses a waveform similarity metric normalized cross-correlation coefficient. Performances of the SRFD algorithm, to reduced the occurrence of errors. The eSRFD algorithm Pass the speech waveform to low-pass filter . The speech waveform is initially low-pass filtered. Each frame of filtered sample data processed by the silence detector. Signal is analysed frame-by-frame; interval 6.4 ms of non-overlapping. R ` a Contains a set of samples s = s i | i 2 @N , ..., N @N Divided 3 consecutive segment
N max S
max Xn= x i = Yn = y i = Zn = z i =
R `a R `a R `a s i @n s i
` `a ` a | i 2 1, ... ,n
S S | i 2 1, ... ,n
a s i+n | i 2 1, ... ,n S Analysis segments for the enhanced super resolution F determinator ` a Normalized cross-correlation for `voiced' frame: If frame of data is not classified as silence or unvoice, then candidate values for the fundamental period by using the firsta ` px,y n normalized cross-correlation of
B C n +L px,y n ` a j=1 ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff vwwww wwwC www www = uB B C n +L n +L u b c2 b c2 u X y jL t X x jL A j=1 j=1 X x jL A jL y b c b c Definition threshold for candidate value Candidate values of the fundamental period are obtained by locating peaks in the normalized crosscorrelation coefficient for which the value of exceeds a specified the threshold. A second normalized cross-correlation coefficient . The `frame is cl...
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This note was uploaded on 02/11/2012 for the course ECE 5525 taught by Professor Staff during the Fall '10 term at FIT.
- Fall '10