An improved method of F0 determination
DOI:
https://doi.org/10.36505/ExLing-2021/12/0027/000500Keywords:
fundamental frequency, sub-harmonic modelling, Chebyshev transformAbstract
This research investigated the structure of the speech Fundamental Frequency (F0). The principal objective of this study was to create an improved method for analyzing, understanding, and plotting the F0 values of spoken words. The F0 is created by a variety of models that produce the F0 values for plotting. These F0 values are a represented average of the lower range frequency of sound.
References
Boyd, J. (2001). Chebyshev and Fourier Spectral Methods. Mineola, NY: Dover.
Gold, B., & Morgan, N. (2000). Speech and Audio Signal Processing. New York: John Wiley & Sons, Inc.
Mannell, R. (2007). Standing waves and resonance. Macquarie University. www.ling.mq.edu.au/speech/acoustics/frequency.
Micheyl, C., Ryan, C., & Oxenham, A. (2012). Further evidence that fundamental-frequency difference limens measure pitch discrimination. Journal of the Acoustical Society of America, 131(5).
Pertusa, A., & Iñesta, J. (2012). Efficient methods for joint estimation of multiple fundamental frequencies in music signals. EURASIP Journal on Advances in Signal Processing, 2012, Article 27.
Roark, R. (2006). Frequency and voice: Perspectives in the time domain. Journal of Voice, 20(3), 325-354.
Staudacher, M., Steixner, V., Griessner, A., & Zierhofer, C. (2016). Fast fundamental frequency determination via adaptive autocorrelation. EURASIP Journal on Audio, Speech, and Music Processing, 2016(17). https://doi.org/10.1186/s13636-016-0095-8
Sun, X. (2002). The Determination, Analysis, and Synthesis of Fundamental Frequency (Doctoral dissertation, Northwestern University).
Titze, I., Riede, T., & Mau, T. (2016). Predicting achievable fundamental frequency ranges in vocalization across species. PLoS Computational Biology, 12(6), e1004907. https://doi.org/10.1371/journal.pcbi.1004907
Trefethen, L. (2000). Spectral Methods in Matlab. Philadelphia, PA: Society for Industrial and Applied Mathematics.
Driscoll, T., Hale, N., & Trefethen, L. (Eds.). (2014). Chebfun Guide.
Tsanas, A., Zañartu, M., Little, M., & McSharry, P. (2012). Robust fundamental frequency estimation in sustained vowels using ensembles. IEEE Transactions on Audio, Speech and Language Processing.
Verde, L., De Pietro, G., & Sannino, G. (2018). A methodology for voice classification based on the personalized fundamental frequency estimation. Biomedical Signal Processing and Control, 42, 134-144.
Downloads
Published
Issue
Section
License
Articles are published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
