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Comparison of tuning frequency estimation methods

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Abstract

In this paper, a comparison of different algorithms for concert pitch (i.e., tuning frequency or reference frequency) estimation is presented and discussed. The unavailability of ground-truth datasets makes this evaluation on real music recordings less trivial than it may initially appear. Hence, in this paper we use two datasets, one of real music (covers80 provided by LabROSA) and one of synthesized music (MS2012, constructed by the authors). The algorithms have been compared in terms of speed of convergence and stability of the estimated value over an increasing length of the analysed signal. A local tuning frequency estimation was also performed in order to compare the ability of the algorithms to follow the local variations of the reference frequency in a real-time environment. Moreover, an analysis of the execution time have been provided. While the various algorithms perform comparably in terms of asymptotic precision, they show a quite different behaviour in terms of speed of convergence and local tuning frequency estimation accuracy.

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Notes

  1. http://www.musescore.com

  2. http://www.fluidsynth.org/

References

  1. Amatriain X, Bonada J, Loscos A, Serra X (2002) DAFX-digital audio effects. In: Z˙olzer U (ed) Spectral processing. Wiley, Chichester, pp 373–438

  2. Degani A (2012) The ‘ms2012’ symbolic music dataset. http://www.ing.unibs.it/alessio.degani/?p=ms2012

  3. Dixon S (1996) A dynamic modelling approach to music recognition. In: Proceedings of the international computer music conference, (ICMC), pp 83–86

  4. Dixon S, Tidhar D, Benetos E (2011) The temperament police: the truth, the ground truth, and nothing but the truth. In: Proceedings of the 12th international conference on music information retrieval, (ISMIR)

  5. Dressler K (2006) Sinusoidal extraction using an efficient implementation of a multi-resolution fft. In: Proceedings of the 9th international conference on digital audio effects, (DAFX)

  6. Dressler K, Streich S (2007) Tuning frequency estimation using circular statistics. In: Proceeding of the 8th international conference on music information retrieval, (ISMIR), pp 357–360

  7. Ellis DPW (2007) The ‘covers80’ cover song data set. http://labrosa.ee.columbia.edu/projects/coversongs/covers80/

  8. Gnann V, Kitza M, Becker J, Spiertz M (2011) Least-squares local tuning frequency estimation for choir music. In: Proceedings of the 131st AES convention

  9. Gómez E (2006) Tonal description of music audio signals. Ph.D. thesis, Universitat Pompeu Fabra, Barcelona

  10. Harte C, Sandler M (2005) Automatic chord identification using a quantised chromagram. In: Proceedings of the 118th AES convention, pp 66–71

  11. ISO (1975) Acoustics - standard tuning frequency (standard musica pitch) ISO 16(1975)

  12. Khadkevich M, Omologo M (2009) Phase-change based tuning for automatic chord recognition. In: Proceedings of the 12th international conference on digital audio effects, (DAFx)

  13. Lee CT, Yang YH, Chen HH (2012) Multipitch estimation of piano music by exemplar-based sparse representation. IEEE Trans Multimed 14(2):608–618

    Google Scholar 

  14. Lerch A (2006) On the requirement of automatic tuning frequency estimation. In: Proceedings of the 7th international conference on music information retrieval, (ISMIR), pp 212–215

  15. Mauch M, Dixon S (2010) Simultaneous estimation of chords and musical context from audio. IEEE Trans Audio Speech Lang Process 18(6):1280–1289

    Google Scholar 

  16. Peeters G (2006) Chroma-based estimation of musical key from audio-signal analysis. In: Proceedings of the 7th international conference on music information retrieval, (ISMIR)

  17. Peeters G (2006) Musical key estimation of audio signal based on hidden markov modeling of chroma vectors. In: Proceedings of the 9th international conference on digital audio effects, (DAFx), pp 127–131

  18. Ryynänen M (2004) Probabilistic modelling of note events in the transcription of monophonic melodies. Master’s thesis, Tampere University of Technology

  19. Serra X (1997) Musical sound modeling with sinusoids plus noise. In: Roads C, Pope ST, Piccialli A, De Poli G (eds) Musical signal processing, chap. Musical sound modeling with sinusoids plus noise. Swets & Zeitlinger Publishers, Netherlands, pp 91–122

  20. Vincent E, Bertin N, Badeau R (2008) Harmonic and inharmonic nonnegative matrix factorization for polyphonic pitch transcription. In: Proceedings of IEEE international conference on acoustics, speech and signal processing (ICASSP), pp 109–112

  21. Zhu Y, Kankanhalli MS, Gao S (2005) Music key detection for musical audio. In: Proceedings of the 11th international conference on multimedia modelling, (MMM), pp 30–37

  22. Zwicker E (2006) Psychoacoustics: facts and models. Springer-Verlag, Berlin, Heidelberg

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Authors and Affiliations

  1. Signals and Communications Lab, Department of Information Engineering (DII), University of Brescia, Via Branze, 38, 25123, Brescia, Italy

    Alessio Degani, Marco Dalai, Riccardo Leonardi & Pierangelo Migliorati

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  1. Alessio Degani
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  2. Marco Dalai
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  3. Riccardo Leonardi
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  4. Pierangelo Migliorati
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Correspondence to Alessio Degani.

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Degani, A., Dalai, M., Leonardi, R. et al. Comparison of tuning frequency estimation methods. Multimed Tools Appl 74, 5917–5934 (2015). https://doi.org/10.1007/s11042-014-1897-2

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