The mel scale (after the word melody)[1] is a perceptual scale of pitches judged by listeners to be equal in distance from one another. The reference point between this scale and normal frequency measurement is defined by assigning a perceptual pitch of 1000 mels to a 1000 Hz tone, 40 dB above the listener's threshold. Above about 500 Hz, increasingly large intervals are judged by listeners to produce equal pitch increments.
Formula
A formula (O'Shaughnessy 1987) to convert f hertz into m mels is[2]
History and other formulas
The formula from O'Shaughnessy's book can be expressed with different logarithmic bases:
The corresponding inverse expressions are
There were published curves and tables on psychophysical pitch scales since Steinberg's 1937[3]
curves based on just-noticeable differences of pitch. More curves soon followed in Fletcher and Munson's 1937[4]
and Fletcher's 1938[5]
and Stevens' 1937[1] and Stevens and Volkmann's 1940[6]
papers using a variety of experimental methods and analysis approaches.
In 1949 Koenig published an approximation based on separate linear and logarithmic segments, with a break at 1000 Hz.[7]
Gunnar Fant proposed the current popular linear/logarithmic formula in 1949, but with the 1000 Hz corner frequency.[8]
An alternate expression of the formula, not depending on choice of logarithm base, is noted in Fant (1968):[9][10]
In 1976, Makhoul and Cosell published the now-popular version with the 700 Hz corner frequency.[11]
As Ganchev et al. have observed, "The formulae [with 700], when compared to [Fant's with 1000], provide a closer approximation of the Mel scale for frequencies below 1000 Hz, at the price of higher inaccuracy for frequencies higher than 1000 Hz."[12] Above 7 kHz, however, the situation is reversed, and the 700 Hz version again fits better.
Data by which some of these formulas are motivated are tabulated in Beranek (1949), as measured from the curves of Stevens and Volkmann:[13]
Beranek 1949 mel scale data from Stevens and Volkmann 1940
Hz
20
160
394
670
1000
1420
1900
2450
3120
4000
5100
6600
9000
14000
mel
0
250
500
750
1000
1250
1500
1750
2000
2250
2500
2750
3000
3250
A formula with a break frequency of 625 Hz is given by Lindsay & Norman (1977);[14] the formula does not appear in their 1972 first edition:
For direct comparison with other formulae, this is equivalent to
Most mel-scale formulas give exactly 1000 mels at 1000 Hz. The break frequency (e.g. 700 Hz, 1000 Hz, or 625 Hz) is the only free parameter in the usual form of the formula. Some non-mel auditory-frequency-scale formulas use the same form but with much lower break frequency, not necessarily mapping to 1000 at 1000 Hz; for example the ERB-rate scale of Glasberg and Moore (1990) uses a break point of 228.8 Hz,[15] and the cochlear frequency–place map of Greenwood (1990) uses 165.3 Hz.[16]
Other functional forms for the mel scale have been explored by Umesh et al.; they point out that the traditional formulas with a logarithmic region and a linear region do not fit the data from Stevens and Volkmann's curves as well as some other forms, based on the following data table of measurements that they made from those curves:[17]
Umesh et al. 1999 mel scale data from Stevens and Volkmann 1940
Hz
40
161
200
404
693
867
1000
2022
3000
3393
4109
5526
6500
7743
12000
mel
43
257
300
514
771
928
1000
1542
2000
2142
2314
2600
2771
2914
3228
Slaney's MATLAB Auditory Toolbox agrees with Umesh et al. and uses the following two-piece fit, though notably not using the "1000 mels at 1000 Hz" convention:[18]
Applications
The first version of Google's Lyra codec uses log mel spectrograms as the feature-extraction step. The transmitted data is a vector-quantized form of the spectrogram, which is then synthesized back to speech by a neural network. Use of the mel scale is believed to weigh the data in a way appropriate to human perception.[19] MelGAN takes a similar approach.[20]
Stevens' student Donald D. Greenwood, who had worked on the mel scale experiments in 1956, considers the scale biased by experimental flaws. In 2009 he posted to a mailing list:[21]
I would ask, why use the Mel scale now, since it appears to be biased? If anyone wants a Mel scale, they should do it over, controlling carefully for order bias and using plenty of subjects – more than in the past – and using both musicians and non-musicians to search for any differences in performance that may be governed by musician/non-musician differences or subject differences generally.
^
Harvey Fletcher; W. A. Munson (1937). "Relation Between Loudness and Masking". Journal of the Acoustical Society of America. 9 (1): 1–10. Bibcode:1937ASAJ....9....1F. doi:10.1121/1.1915904.
^
Stevens, S.; Volkmann, J. (1940). "The Relation of Pitch to Frequency: A Revised Scale". American Journal of Psychology. 53 (3): 329–353. doi:10.2307/1417526. JSTOR1417526.
^
W. Koenig (1949). "A new frequency scale for acoustic measurements". Bell Telephone Laboratory Record. 27: 299–301.
^
Gunnar Fant (1949) "Analys av de svenska konsonantljuden : talets allmänna svängningsstruktur", LM Ericsson protokoll H/P 1064.
^Fant, Gunnar. (1968). Analysis and synthesis of speech processes. In B. Malmberg (ed.), Manual of phonetics (pp. 173–177). Amsterdam: North-Holland.
^John Makhoul; Lynn Cosell (1976). "LPCW: An LPC vocoder with linear predictive spectral warping". ICASSP '76. IEEE International Conference on Acoustics, Speech, and Signal Processing. Vol. 1. IEEE. pp. 466–469. doi:10.1109/ICASSP.1976.1170013.
^
T. Ganchev; N. Fakotakis; G. Kokkinakis (2005), "Comparative evaluation of various MFCC implementations on the speaker verification task", Proceedings of the SPECOM-2005, pp. 191–194, CiteSeerX10.1.1.75.8303
^Beranek, Leo L. (1949). Acoustic measurements. New York: McGraw-Hill.
^Lindsay, Peter H.; & Norman, Donald A. (1977). Human information processing: An introduction to psychology (2nd ed.). New York: Academic Press.
^B. C. J. Moore and B. R. Glasberg, "Suggested formulae for calculating auditory-filter bandwidths and excitation patterns", Journal of the Acoustical Society of America 74: 750–753, 1983.
^Greenwood, D. D. (1990). A cochlear frequency–position function for several species—29 years later. The Journal of the Acoustical Society of America, 87, 2592–2605.
^Slaney, M. Auditory Toolbox: A MATLAB Toolbox for Auditory Modeling Work. Technical Report, version 2, Interval Research Corporation, 1998., translated to Python in librosa (librosa documentation).