Statistical analysis for the pitch of mask-wearing Arabic speech

According to Fourier analysis, any periodic function can be analyzed as an infinite series of trigonometric functions (sets of sines and cosines). The kernel of decay cosine yields an extension for the previous frequency-based, sieve-type detection algorithm by giving smooth peaks for decaying ampli...

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Bibliographic Details
Published inTelkomnika Vol. 20; no. 4; pp. 846 - 857
Main Authors Kadhim, Hasan M., Ahmed, Alaa H., Abdulhussien, Saif A.
Format Journal Article
LanguageEnglish
Published Yogyakarta Ahmad Dahlan University 01.08.2022
Subjects
Accuracy
Algorithms
Amplitudes
COVID-19
Cross correlation
Fourier analysis
Harmony (Music)
Hypotheses
Infinite series
Linear prediction
Males
Optimization
Periodic functions
Sampling
Signal processing
Speaking
Speech
Statistical analysis
Trigonometric functions
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Summary:According to Fourier analysis, any periodic function can be analyzed as an infinite series of trigonometric functions (sets of sines and cosines). The kernel of decay cosine yields an extension for the previous frequency-based, sieve-type detection algorithm by giving smooth peaks for decaying amplitudes with the harmonics of the signal correlation. The sequential outline of the RAPT algorithm is: 1) Providing speech samples with their sampling rate and with a reduced sampling rate. 2) Periodically, computing normalized cross-correlation function (NCCF) of the reduced sampling rate speech signal with lags in the F0 range. 3) Indicating the locations of maximum at the 1st pass of NCCF. 4) For the vicinity of the peaks in that 1st pass, calculate the NCCF for the original sampling rate. 5) Again, finding the maximum in that NCCF. Obtaining the location and amplitude of the modified peak. 6) For each peak obtained from the NCCF (high resolution), estimate the F0 of the processed frame. 7) The hypothesis of the frame for unvoiced/voiced is advanced for each frame. 8) Finding the group of the NCCF peaks via optimization process for the unvoiced/voiced hypotheses for all the frames which have the best match with the above characteristics. 9) Using the well-known speech pitch tracking algorithm (PTA), RAPT has the following differences: - PTA computes the NCCF in the linear prediction coding (LPC).
ISSN:1693-6930
2302-9293
DOI:10.12928/telkomnika.v20i4.22071