Pitch Estimation by Enhanced Super Resolution determinator

Pitch Estimation by Enhanced Super Resolution determinator

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Unformatted text preview: subsequent q n1 ` a In the case of only 1 candidate score 1 but no candidate score2, the frame status will be reconsidered depends on the frames state of previous frame. If the previous frame is `silent', the current value is hold and depends on the next frame. If the next frame is also `silent', the current frame will be considered as `silent'. Otherwise, the current frame is considered as `voiced' and the held will be considered as the good estimation for the current frame. Modification apply biasing to and Biasing is applied if the following conditions The two previous frames were classified as `voiced' The value of the previous frame is not being temporarily held. ` a The F of previous frame f. 0 is less than 7/4 *( of its preceding voiced frame f. 0) , and greater than 5/8* f. 0 The biasing tends to increase the percentage of unvoiced regions of speech being incorrectly classified as `voiced'. Calculate the fundamental period: The fundamental period for the frame is estimated ` a by calculate r x,y n wwwwwwwwwwwwwww wwwwwwwwwwwwwww wwwwwwwwwwwwwww wwwwwwwwwwwwwww wwwwwwwwwwwwww r x,y n = vwwwwwwwwwwwwwwwwwww u n b c2 n b c2 u X y j t X x j A j=1 j=1 ` a j=1 ffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffffff X x j A j y n b c b c Implementation In this report will be cover the eSRFD algorithm, implementation by MATLAB ver 7.2b to program following by eSRFD algoithm The Result The Result Conclusion The acoustic correlate of pitch is the fundamental frequency...
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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.

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