The equivalent rectangular bandwidth or ERB is a measure used in psychoacoustics, which gives an approximation to the bandwidths of the filters in human hearing, using the unrealistic but convenient simplification of modeling the filters as rectangular band-pass filters, or band-stop filters, like in tailor-made notched music training (TMNMT).

Approximations

For moderate sound levels and young listeners, Moore & Glasberg (1983) suggest that the bandwidth of human auditory filters can be approximated by the polynomial equation:

E R B ⁡ ( F ) = 6.23 ⋅ F 2 + 93.39 ⋅ F + 28.52 {\displaystyle \operatorname {\mathsf {ERB}} (\ F\ )=6.23\cdot F^{2}+93.39\cdot F+28.52}

where F is the center frequency of the filter, in kHz, and ERB( F ) is the bandwidth of the filter in Hz. The approximation is based on the results of a number of published simultaneous masking experiments and is valid from 0.1–6500Hz.

Seven years later, Glasberg & Moore (1990) published another, simpler approximation:

E R B ⁡ ( f ) = 24.7 H z ⋅ ( 4.37 ⋅ f 1000 H z + 1 ) {\displaystyle \,\operatorname {\mathsf {ERB}} (\ f\ )=24.7\ {\mathsf {Hz}}\ \cdot \left({\frac {4.37\cdot f}{\ 1000\ {\mathsf {Hz}}\ }}+1\right)\,}

where f is in Hz and ERB(f) is also in Hz. The approximation is applicable at moderate sound levels and for values of f between 100 and 10000Hz.

ERB-rate scale

The ERB-rate scale, or ERB-number scale, can be defined as a function ERBS(f) which returns the number of equivalent rectangular bandwidths below the given frequency f. The units of the ERB-number scale are known ERBs, or as Cams, following a suggestion by Hartmann. The scale can be constructed by solving the following differential system of equations:

{ E R B S ( 0 ) = 0 d f d E R B S ( f ) = E R B ( f ) {\displaystyle {\begin{cases}\mathrm {ERBS} (0)=0\\{\frac {df}{d\mathrm {ERBS} (f)}}=\mathrm {ERB} (f)\\\end{cases}}}

The solution for ERBS(f) is the integral of the reciprocal of ERB(f) with the constant of integration set in such a way that ERBS(0) = 0.

Using the second order polynomial approximation (Eq.1) for ERB(f) yields:

E R B S ( f ) = 11.17 ⋅ ln ⁡ ( f + 0.312 f + 14.675 ) + 43.0 {\displaystyle \mathrm {ERBS} (f)=11.17\cdot \ln \left({\frac {f+0.312}{f+14.675}}\right)+43.0}

where f is in kHz. The VOICEBOX speech processing toolbox for MATLAB implements the conversion and its inverse as:

E R B S ( f ) = 11.17268 ⋅ ln ⁡ ( 1 + 46.06538 ⋅ f f + 14678.49 ) {\displaystyle \mathrm {ERBS} (f)=11.17268\cdot \ln \left(1+{\frac {46.06538\cdot f}{f+14678.49}}\right)}

f = 676170.4 47.06538 − e 0.08950404 ⋅ E R B S ( f ) − 14678.49 {\displaystyle f={\frac {676170.4}{47.06538-e^{0.08950404\cdot \mathrm {ERBS} (f)}}}-14678.49}

where f is in Hz.

Using the linear approximation (Eq.2) for ERB(f) yields:

E R B S ( f ) = 21.4 ⋅ log 10 ⁡ ( 1 + 0.00437 ⋅ f ) {\displaystyle \mathrm {ERBS} (f)=21.4\cdot \log _{10}(1+0.00437\cdot f)}

where f is in Hz.

See also

External links

  • Hartmut Traunmüller (1997). . Phonetics at Stockholm University. Archived from on 2011-04-27.
  • by Giampiero Salvi: shows comparison between Bark, Mel, and ERB scales