cochleagram.tar.gz_Gammatone_cochleagram_cochleagram.tar_gammato

****************************************************************************** **** Matlab Toolbox for Cochleagram Analysis and Synthesis **** **** (including ideal binary mask, or IBM, processing) **** **** **** **** Written by DeLiang Wang, 2/2007 (at Oticon), and adapted by **** **** John Woodruff, 11/2008 **** **** Based on codes provided by Zhaozhang Jin and earlier versions in C **** ****************************************************************************** The toolbox contains the following Matlab functions: gammatone.m - Produce an array of filtered responses from a Gammatone filterbank. meddis.m - Produce auditory nerve response from output of a Gammatone filterbank. cochleagram.m - Produce a cochleagram from output of a Gammatone filterbank. ibm.m - Produce an IBM processed mixture. synthesis.m - Resynthesize a waveform signal from a mixture signal and a binary mask. cochplot.m - Display the image of a cochleagram with proper coordinate labels erb2hz.m - Convert ERB-rate scale to normal frequency scale. hz2erb.m - Convert normal frequency scale in hz to ERB-rate scale. loudness.m - Compute loudness level in Phons on the basis of equal-loudness functions. In addition, f_af_bf_cf.mat - Contains parameter values of equal-loudness functions from BS3383, "Normal equal-loudness level contours for pure tones under free-field listening conditions", table 1. Examples on how to use the toolbox: * To genenarate and display a cochleagram without hair cell transduction, type the following: gf = gammatone(Signal); cg = cochleagram(gf); cochplot(cg); * To genenarate and display a cochleagram with hair cell transduction, type the following: gf = gammatone(inputSignal); hc = meddis(gf); cg = cochleagram(hc); cochplot(cg); Other comments: - When using Matlab function 'wavread', the amplitudes are limited to the range [-1,+1], which are much smaller than original integers coded in a wavefile. It is important, particularly for hair cell transduction, that the amplitudes are scaled up to the original range. With 16-bit precision, the scaling can be simply done by multiplying with power(2, 15), or Matlab function 'pow2(15)'. - The Matlab version is several times slower than C/C++ version, which is downloadable from http://www.cse.ohio-state.edu/pnl/software.html (follow "Voiced speech segregation"). - More detailed comments for each function are given in the M-file. - For a tutorial introduction of the meaning of these functions see: D.L. Wang and G.J. Brown (2006): "Fundamentals of computational auditory scene analysis," In D.L. Wang and G.J. Brown (eds.): Computational Auditory Scene Analysis: Principles, Algorithms, and Applications (Chapter 1, pp. 1-44). Wiley/IEEE Press, Hoboken NJ (Website: www.casabook.org).