![]() ![]() A non-parametric Friedman’s test of differences among repeated measures was conducted. Acoustic parameters of F0, F0 min, F0 max, I0, I0 min, I0 max, JF0, JT0, RAP3, RAP5, SHdB, APQ5, APQ11, HNR, and GNE were compared in all the different conditions mentioned above. The four conditions used were deletion of F1, deletion of F2, deletion of F3, and deletion of F1, F2, and F3 formants. Formant deletion was accomplished using manual methods. In the FBIF-based method, the recorded voice sample was analyzed under four different conditions, i.e., by deleting different formants from the sample. However, in the current study, the number of LPCs was set to 14, 16, 18, 20, and 22, respectively in each of the analysis conditions with other settings remaining the same. The standard value of LPC used in the Vaghmi software is 18. In the LPBIF-based method, the recorded voice sample was analyzed under five different conditions, i.e., by varying the number of LPCs. Phonation samples of /a/ at a comfortable pitch and loudness by 30 healthy participants (15 males and 15 females) were recorded on to a PC in a noise-free environment. The effects of formant deletion and number of LPCs on the various vocal parameters-Fundamental frequency based, intensity based, perturbation based, and noise-based measures-were studied. This study aims at describing effects of the two available methods of inverse filtering-Formant-Based Inverse Filtering (FBIF) and Linear Prediction-Based Inverse Filtering (LPBIF) on acoustic parameters. The estimation of glottal flow parameters using acoustic analysis is achieved through the method of Inverse Filtering (IF). Acoustic analysis is one of the efficient, non-invasive, and quantitative methods of voice assessment. ![]()
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