The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
YIN, a fundamental frequency estimator for speech and music
Abstract
An algorithm is presented for the estimation of the fundamental frequency (F0) of speech or musical sounds. It is based on the well-known autocorrelation method with a number of modifications that combine to prevent errors. The algorithm has several desirable features. Error rates are about three times lower than the best competing methods, as evaluated over a database of speech recorded together with a laryngograph signal. There is no upper limit on the frequency search range, so the algorithm is suited for high-pitched voices and music. The algorithm is relatively simple and may be implemented efficiently and with low latency, and it involves few parameters that must be tuned. It is based on a signal model (periodic signal) that may be extended in several ways to handle various forms of aperiodicity that occur in particular applications. Finally, interesting parallels may be drawn with models of auditory processing.
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Cites
Kawahara, H., Masuda-Katsuse, I., & de Cheveigné, A. (1999) · Speech Communication · doi:10.1016/s0167-6393(98)00085-5 · Cited by 1,831
Self-citationBoersma, P. (1993) · Cited by 1,046
Noll, A. M. (1967) · The Journal of the Acoustical Society of America · doi:10.1121/1.1910339 · Cited by 806
Pitch, consonance, and harmony
Terhardt, E. (1974) · The Journal of the Acoustical Society of America · doi:10.1121/1.1914648 · Cited by 701
A duplex theory of pitch perception
Licklider, J. C. R. (1951) · Experientia · doi:10.1007/bf02156143 · Cited by 529
Meddis, R., & Hewitt, M. J. (1991) · The Journal of the Acoustical Society of America · doi:10.1121/1.400725 · Cited by 519
Average magnitude difference function pitch extractor
Ross, M., Shaffer, H., Cohen, A., Freudberg, R., & Manley, H. (1974) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1974.1162598 · Cited by 490
Neural correlates of the pitch of complex tones. I. Pitch and pitch salience
Cariani, P. A., & Delgutte, B. (1996) · Journal of Neurophysiology · doi:10.1152/jn.1996.76.3.1698 · Cited by 432
Measurement of pitch by subharmonic summation
Hermes, D. J. (1988) · The Journal of the Acoustical Society of America · doi:10.1121/1.396427 · Cited by 312
Culling, J. F., & Summerfield, Q. (1995) · The Journal of the Acoustical Society of America · doi:10.1121/1.413571 · Cited by 204
Cited by
Social context-induced song variation affects female behavior and gene expression
Woolley, S. C., & Doupe, A. J. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060062 · Cited by 303
López-de-Ipiña, K., Alonso, J.-B., Travieso, C., Solé-Casals, J., Egiraun, H., Faundez-Zanuy, M., Ezeiza, A., Barroso, N., Ecay-Torres, M., Martinez-Lage, P., et al. (2013) · Sensors · doi:10.3390/s130506730 · Cited by 190
Voice Disorder Identification by Using Machine Learning Techniques
Verde, L., De Pietro, G., & Sannino, G. (2018) · IEEE Access · doi:10.1109/access.2018.2816338 · Cited by 156
López-de-Ipiña, K., Alonso, J. B., Solé-Casals, J., Barroso, N., Henriquez, P., Faundez-Zanuy, M., Travieso, C. M., Ecay-Torres, M., Martínez-Lage, P., & Eguiraun, H. (2015) · Cognitive Computation · doi:10.1007/s12559-013-9229-9 · Cited by 132
Neural networks involved in voluntary and involuntary vocal pitch regulation in experienced singers
Zarate, J. M., Wood, S., & Zatorre, R. J. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2009.10.025 · Cited by 131
Metadata
- Authors
- de Cheveigné, A., & Kawahara, H.
- Venue
- The Journal of the Acoustical Society of America
- Publisher
- Acoustical Society of America (ASA)
- Published
- 2002-04-01
- Volume
- 111
- Issue
- 4
- Pages
- 1917-1930
- ISSN
- 0001-4966 (ISSN-L)
- 1520-8524
- OpenAlex
- W2091425152
- Cited by
- 1,920
- References
- 17
- FWCI
- 40.72
- Type
- journal article
- Language
- en
- Open access
- closed
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- de Cheveigné, A., & Kawahara, H. (2002). YIN, a fundamental frequency estimator for speech and music. The Journal of the Acoustical Society of America. https://doi.org/10.1121/1.1458024
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
