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Better README.md
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JacobD10 committed Jul 13, 2017
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2 changes: 1 addition & 1 deletion ALcons2STI.m
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function [ STIval ] = ALcons2STI( ALcons )
%ALCONS2STI Converts Articulation Loss of Consonants (ALcons) to the Speech Transmission Index (STI)
% Converts Articulation Loss of Consonants (ALcons) to the Speech Transmission Index (STI)
%
% Syntax: [STIval] = ALcons2STI( ALcons )
% Pass the Articulation Loss of Consonants (ALcons) value to the
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2 changes: 1 addition & 1 deletion ArbitraryOctaveFilt.m
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function y = ArbitraryOctaveFilt(x, SPECT, FREQS, N, fs, octBandwidth)
%ARBITRARYOCTAVEFILT Filters a signal with any arbitrary spectrum smoothed with any fractional octave band average
% Filters a signal with any arbitrary spectrum smoothed with any fractional octave band average
%
% Syntax: Y = ARBITRARYOCTAVEFILT(X, SPECT, FREQS, N, FS, OCTBANDWIDTH)
%
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2 changes: 1 addition & 1 deletion COSHdist.m
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function [E,Eps] = COSHdist(H,P)
%COSHDIST Finds the symmetric Itakura-Saito distance using the hyperbolic cosine function
% Finds the symmetric Itakura-Saito distance using the hyperbolic cosine function
%
% Syntax: [OUTPUTARGS] = COSHDIST(INPUTARGS) Explain usage here
%
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2 changes: 1 addition & 1 deletion ConcatTIMITtalkers.m
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function ConcatTIMITtalkers( TIMITdir, OutDir )
%CONCATTIMITTALKERS Concatenates all the talkers from the TIMIT corpus into individual speech files
% Concatenates all the talkers from the TIMIT corpus into individual speech files
%
% Syntax: CONCATTIMITTALKERS( TIMITDIR, OUTDIR )
%
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4 changes: 2 additions & 2 deletions Correlated_Normalisation.m
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function [ X_Approx_Adjust, Scaling_Factor ] = Correlated_Normalisation( X, X_Approx )
%CORRELATED_NORMALISATION Matches the amplitude of X using cross-correlation
function [ X_Approx_Adjust, Scaling_Factor ] = correlated_normalisation( X, X_Approx )
% Matches the amplitude of X using cross-correlation
%
% Syntax: [ X_Approx_Adjust, Scaling_Factor ] = CORRELATED_NORMALISATION( X, X_Approx )
%
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2 changes: 1 addition & 1 deletion Dropbox.m
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function [ res, cmd_out ] = Dropbox( action )
%DROPBOX Function to start and kill dropbox from MATLAB
% Function to start and kill dropbox from MATLAB
%
% Syntax: [ res, cmd_out ] = Dropbox( action )
%
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2 changes: 1 addition & 1 deletion IRcompactingKirkebyFilter.m
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function [ filt ] = IRcompactingKirkebyFilter( ir, ir_len, f_band, fs, reg )
%COMPACTINGKIRKEBYFILTER
% Compacting Kirkeby Filter

% Regularisation parameter
ereg = epsreg(ir_len*fs,f_band,fs,reg);
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2 changes: 1 addition & 1 deletion LTASS.m
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function [ spect, frqs ] = LTASS( speech_folder_OR_vec, nfft, fs )
%LTASS Computes the Long-Term Average Speech Spectrum from a folder of speech files or vector of speech samples
% Computes the Long-Term Average Speech Spectrum from a folder of speech files or vector of speech samples
%
% Syntax: [ spect, frqs ] = LTASS( speech_folder_OR_vec, nfft )
%
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2 changes: 1 addition & 1 deletion MiKTeX_FNDB_Refresh.m
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function [ res, cmd_out ] = MiKTeX_FNDB_Refresh( )
%MiKTeX_FNDB_Refresh Function to refresh the File Name DataBase in MiKTeX
% Function to refresh the File Name DataBase in MiKTeX
%
% Syntax: [ res, cmd_out ] = MiKTeX_FNDB_Refresh() This is used after
% exporting a file (i.e. figure) to a tex directory so that a direct comilation
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82 changes: 42 additions & 40 deletions README.md
@@ -1,47 +1,49 @@
# SoundZone_Tools
# Sound Zone Tools
Sound Zone Tools is a collection of auxiliary MATLAB tools for soundfield reproduction and other signal processing tasks. The tools have been written by myself or collected from other open sources. If a file is missing and there is no download link in the parent file's header, please open an issue to request the link.

Don't forget to give appropriate reference to the code used, author details are usually found in the file's header.
Enjoy!

File name | Description
:--------:|------------
_addNoise.m_ | ADDNOISE Adds a given level and type of noise to a signal
_ALcons2STI.m_ | ALCONS2STI Converts Articulation Loss of Consonants (ALcons) to the Speech Transmission Index (STI)
_ArbitraryOctaveFilt.m_ | ARBITRARYOCTAVEFILT Filters a signal with any arbitrary spectrum smoothed with any fractional octave band average
_ConcatTIMITtalkers.m_ | CONCATTIMITTALKERS Concatenates all the talkers into single speech files in the TIMIT database
_confidence_intervals.m_ | CONFIDENCE_INTERVALS Find the confidence intervals for a set of data for use with the errorbar function in MATLAB
_Correlated_Normalisation.m_ | CORRELATED_NORMALISATION Matches the amplitude of X using cross-correlation
_COSHdist.m_ | COSHDIST Finds the symmetric Itakura-Saito distance using the hyperbolic cosine function
_Dropbox.m_ | DROPBOX Function to start and kill dropbox from MATLAB
_estoi.m_ | ESTOI Implementation of the Extended Short-Time Objective Intelligibility (ESTOI) predictor
_extractIR.m_ | EXTRACTIR Extract impulse response from swept-sine response.
_fconv.m_ | FCONV Fast Parallelised Convolution
_fdeconv.m_ | FDECONV Fast Parallelised Deconvolution
_generateNoise.m_ | ADDNOISE Generates basic noise at a given level with the option to be additive
_getAllFiles.m_ | GETALLFILES Retrieves a list of all files within a directory
_interpFromVal_2D.m_ | INTERPFROMVAL_2D This function will interpolate from desired z-axis values and return the interpolation indices for them in the y-axis
_interpVal.m_ | INTERPVAL This function will interpolate from desired arbitrarily spaced index values
_interpVal_2D.m_ | INTERPVAL_2D This function will interpolate from desired abitrarily spaced index values in a 2D array
_invFIR.m_ | INVFIR design inverse filter (FIR) from mono or stereo impulse response
_invimplms.m_ | INVIMPLMS Inverse impulse using the Levinson-Durbin algorithm
_invSweepFFT.m_ | INVSWEEPFFT Obtain the FFT of an inverted exponentional sine sweep
_IRcompactingKirkebyFilter.m_ | COMPACTINGKIRKEBYFILTER
_keepFilesFromFolder.m_ | KEEPFILESFROMFOLDER Keeps files and file paths in a cell array if the file names in a given folder are found in the path string
_LTASS.m_ | LTASS Computes the Long-Term Average Speech Spectrum from a folder of speech files or vector of speech samples
_MiKTeX_FNDB_Refresh.m_ | MiKTeX_FNDB_Refresh Function to refresh the File Name DataBase in MiKTeX
_octaveBandMean.m_ | OCTAVEBANDMEAN Given a magnitude spectrum this function will calculate the average (single, third, nth) octave band magnitude
_pesq2.m_ | PESQ objective speech quality measure
_pesq3.m_ | PESQ3 A wrapper for the objective Perceptual Evaluation of Speech Quality measure
_pesq_mex_vec.m_ | PESQ_MEX_VEC Accepts vectors for a mex compiled version of the objective Perceptual Evaluation of Speech Quality measure
_printHyperlink.m_ | PRINTHYPERLINK Prints a hyperlink to the command window
_shapeSpectrum.m_ | SHAPESPECTRUM This function will shape an input signal to the given spectrum (simple, unregulated spectral shaping)
_showTimeToCompletion.m_ | SHOWTIMETOCOMPLETION Prints the time to completion and expected finish of a looped simulation based on linear extrapolation.
_simpleWarning.m_ | SIMPLEWARNING Prints a coloured warning without the location information
_sineSweepLin.m_ | SINESWEEP_LIN Synthesize a linear sine sweep
_STI.m_ | STI Calculation of the Speech Transmission Index (STI)
_STI_BandFilters.m_ | STI_BandFilters Calculation of the Speech Transmission Index (STI) Band Filters
_stoi.m_ | STOI The Short-Time Objective Intelligibility measure
_stoi_d2percCorr.m_ | STOI_D2PERCCORR Converts the stoi measure, d, to percent words correct unit
_synthSweep.m_ | SYNTHSWEEP Synthesize a logarithmic sine sweep
_wait_for_file.m_ | WAIT_FOR_FILE A forceful method to wait for a file to finish being written to
_addNoise.m_ | Adds a given level and type of noise to a signal
_ALcons2STI.m_ | Converts Articulation Loss of Consonants (ALcons) to the Speech Transmission Index (STI)
_ArbitraryOctaveFilt.m_ | Filters a signal with any arbitrary spectrum smoothed with any fractional octave band average
_buildDocumentation.m_ | Generates documentation HTML and builds MATLAB search database for dependencies of a main file
_buildReleaseZIP.m_ | Creates a ZIP file of all release dependencies for a main file
_ConcatTIMITtalkers.m_ | Concatenates all the talkers from the TIMIT corpus into individual speech files
_confidence_intervals.m_ | Find the confidence intervals for a set of data for use with the errorbar function in MATLAB
_correlated_normalisation.m_ | Matches the amplitude of X using cross-correlation
_COSHdist.m_ | Finds the symmetric Itakura-Saito distance using the hyperbolic cosine function
_Dropbox.m_ | Function to start and kill dropbox from MATLAB
_estoi.m_ | Implementation of the Extended Short-Time Objective Intelligibility (ESTOI) predictor
_extractIR.m_ | Extract impulse response from swept-sine response.
_fconv.m_ | Fast Parallelised Convolution
_fdeconv.m_ | Fast Parallelised Deconvolution
_generateNoise.m_ | Generates basic noise at a given level with the option to be additive
_getAllFiles.m_ | Retrieves a list of all files within a directory
_interpFromVal_2D.m_ | This function will interpolate from desired z-axis values and return the interpolation indices for them in the y-axis
_interpVal.m_ | This function will interpolate from desired arbitrarily spaced index values
_interpVal_2D.m_ | This function will interpolate from desired abitrarily spaced index values in a 2D array
_invFIR.m_ | Design inverse filter (FIR) from mono or stereo impulse response
_invimplms.m_ | Inverse impulse using the Levinson-Durbin algorithm
_invSweepFFT.m_ | Obtain the FFT of an inverted exponentional sine sweep
_IRcompactingKirkebyFilter.m_ | Compacting Kirkeby Filter
_keepFilesFromFolder.m_ | Keeps files and file paths in a cell array if the file names in a given folder are found in the path string
_LTASS.m_ | Computes the Long-Term Average Speech Spectrum from a folder of speech files or vector of speech samples
_MiKTeX_FNDB_Refresh.m_ | Function to refresh the File Name DataBase in MiKTeX
_octaveBandMean.m_ | Given a magnitude spectrum this function will calculate the average (single, third, nth) octave band magnitude
_pesq2.m_ | Objective speech quality measure
_pesq3.m_ | A wrapper for the objective Perceptual Evaluation of Speech Quality measure
_pesq_mex_vec.m_ | Accepts vectors for a mex compiled version of the objective Perceptual Evaluation of Speech Quality measure
_printHyperlink.m_ | Prints a hyperlink to the command window
_shapeSpectrum.m_ | This function will shape an input signal to the given spectrum (simple, unregulated spectral shaping)
_showTimeToCompletion.m_ | Prints the time to completion and expected finish of a looped simulation based on linear extrapolation.
_simpleWarning.m_ | Prints a coloured warning without the location information
_sineSweepLin.m_ | Synthesize a linear sine sweep
_STI.m_ | Calculation of the Speech Transmission Index (STI)
_STI_BandFilters.m_ | Calculation of the Speech Transmission Index (STI) Band Filters
_stoi.m_ | The Short-Time Objective Intelligibility measure
_stoi_d2percCorr.m_ | Converts the stoi measure, d, to percent words correct unit
_synthSweep.m_ | Synthesize a logarithmic sine sweep
_wait_for_file.m_ | A forceful method to wait for a file to finish being written to
2 changes: 1 addition & 1 deletion STI.m
@@ -1,5 +1,5 @@
function [ STI_val, ALcons, STI_val_approx, ALcons_approx ] = STI( ImpulseResponse, fs, OctaveFilters )
%STI Calculation of the Speech Transmission Index (STI)
% Calculation of the Speech Transmission Index (STI)
%
% Syntax: [STI_val, ALcons, STI_val_approx, ALcons_approx] = STI(ImpulseResponse, fs, OctaveFilters)
% This function calculates the Speech Transmission Index from a given
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2 changes: 1 addition & 1 deletion STI_BandFilters.m
@@ -1,5 +1,5 @@
function OctaveFilters = STI_BandFilters( N, fs )
%STI_BandFilters Calculation of the Speech Transmission Index (STI) Band Filters
% Calculation of the Speech Transmission Index (STI) Band Filters
%
% Syntax: OctaveFilters = STI_BandFilters( N, fs )
% This function calculates the Speech Transmission Index octave band
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2 changes: 1 addition & 1 deletion addNoise.m
@@ -1,5 +1,5 @@
function [x_n] = addNoise( x, level, type )
%ADDNOISE Adds a given level and type of noise to a signal
% Adds a given level and type of noise to a signal
%
% Syntax: [x_n] = ADDNOISE( x, level, type ) Pass the signal, x, level
% and type of noise to the function and x_n will be the resulting signal
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2 changes: 1 addition & 1 deletion confidence_intervals.m
@@ -1,5 +1,5 @@
function [ Conf_intervals ] = confidence_intervals( samples, interval, islognorm )
%CONFIDENCE_INTERVALS Find the confidence intervals for a set of data for use with the errorbar function in MATLAB
% Find the confidence intervals for a set of data for use with the errorbar function in MATLAB
%
% Syntax: [Conf_intervals] = CONFIDENCE_INTERVALS( samples, interval )
% Pass the samples to the function with the desired confidence interval (95
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2 changes: 1 addition & 1 deletion estoi.m
@@ -1,5 +1,5 @@
function d = estoi(x, y, fs_signal)
%ESTOI Implementation of the Extended Short-Time Objective Intelligibility (ESTOI) predictor
% Implementation of the Extended Short-Time Objective Intelligibility (ESTOI) predictor
% d = estoi(x, y, fs_signal) returns the output of the extended short-time
% objective intelligibility (ESTOI) predictor.
%
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2 changes: 1 addition & 1 deletion extractIR.m
@@ -1,5 +1,5 @@
function [irLin, irNonLin] = extractIR(sweep_response, invsweepfft)
% EXTRACTIR Extract impulse response from swept-sine response.
% Extract impulse response from swept-sine response.
% [irLin, irNonLin] = extractIR(sweep_response, invsweepfft)
% Extracts the impulse response from the swept-sine response. Use
% synthSweep.m first to create the stimulus; then pass it through the
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2 changes: 1 addition & 1 deletion fconv.m
@@ -1,5 +1,5 @@
function [y]=fconv(x, h)
%FCONV Fast Parallelised Convolution
% Fast Parallelised Convolution
% [y] = FCONV(x, h) convolves x and h in the frequency domain
% to +-1.
%
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2 changes: 1 addition & 1 deletion fdeconv.m
@@ -1,5 +1,5 @@
function [h]=fdeconv(x, y)
%FDECONV Fast Parallelised Deconvolution
% Fast Parallelised Deconvolution
% [h] = FDECONV(x, y) deconvolves x and y in the frequency domain
%
% x = input vector (original)
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2 changes: 1 addition & 1 deletion generateNoise.m
@@ -1,5 +1,5 @@
function [n_] = generateNoise( x, level, type, add )
%ADDNOISE Generates basic noise at a given level with the option to be additive
% Generates basic noise at a given level with the option to be additive
%
% Syntax: [n_] = GENERATENOISE( x, level, type, add ) Pass the signal, x, level
% and type of noise to the function and n_ will be the resulting noise.
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2 changes: 1 addition & 1 deletion getAllFiles.m
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function fileList = getAllFiles(dirPath)
%GETALLFILES Retrieves a list of all files within a directory
% Retrieves a list of all files within a directory
%
% Syntax: fileList = getAllFiles(dirName)
%
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2 changes: 1 addition & 1 deletion interpFromVal_2D.m
@@ -1,5 +1,5 @@
function [ interpolated_index_values2 ] = interpFromVal_2D( values, index_values1, index_values2, desired_index_values1, desired_values2 )
%INTERPFROMVAL_2D This function will interpolate from desired z-axis values and return the interpolation indices for them in the y-axis
% This function will interpolate from desired z-axis values and return the interpolation indices for them in the y-axis
%
% Syntax: [ interpolated_values ] = interpFromVal_2D( values, index_values1, index_values2, desired_index_values1, desired_index_values2 )
%
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2 changes: 1 addition & 1 deletion interpVal.m
@@ -1,5 +1,5 @@
function [ interpolated_values, interpolated_indices] = interpVal( values, index_values, desired_index_values )
%INTERPVAL This function will interpolate from desired arbitrarily spaced index values
% This function will interpolate from desired arbitrarily spaced index values
%
% Syntax: [ interpolated_values, interpolated_indices] = interpVal( values, index_values, desired_index_values )
%
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2 changes: 1 addition & 1 deletion interpVal_2D.m
@@ -1,5 +1,5 @@
function [ interpolated_values ] = interpVal_2D( values, index_values1, index_values2, desired_index_values1, desired_index_values2, interpolation_type )
%INTERPVAL_2D This function will interpolate from desired abitrarily spaced index values in a 2D array
% This function will interpolate from desired abitrarily spaced index values in a 2D array
%
% Syntax: [ interpolated_values ] = interpVal_2D( values, index_values1, index_values2, desired_index_values1, desired_index_values2, interpolation_type )
%
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2 changes: 1 addition & 1 deletion invFIR.m
@@ -1,5 +1,5 @@
function [ih]=invFIR(type,h,Nfft,Noct,L,range,reg,window)
%INVFIR design inverse filter (FIR) from mono or stereo impulse response
% Design inverse filter (FIR) from mono or stereo impulse response
% ------------------------------------------------------------------------------
% description: design inverse filter (FIR) from mono or stereo impulse response
% ------------------------------------------------------------------------------
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2 changes: 1 addition & 1 deletion invSweepFFT.m
@@ -1,5 +1,5 @@
function [ invirfft ] = invSweepFFT( y, f1, f2, fs, Nfft )
%INVSWEEPFFT Obtain the FFT of an inverted exponentional sine sweep
% Obtain the FFT of an inverted exponentional sine sweep
% Detailed explanation goes here
if nargin < 5
Nfft = length(y);
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2 changes: 1 addition & 1 deletion invimplms.m
@@ -1,5 +1,5 @@
function inv=invimplms(den,n,d)
%INVIMPLMS Inverse impulse using the Levinson-Durbin algorithm
% Inverse impulse using the Levinson-Durbin algorithm
% syntax inv=invimplms(den,n,d)
% den - denominator impulse
% n - length of result
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2 changes: 1 addition & 1 deletion keepFilesFromFolder.m
@@ -1,5 +1,5 @@
function [Files] = keepFilesFromFolder( FileList, KeepFromFolder )
%KEEPFILESFROMFOLDER Keeps files and file paths in a cell array if the file names in a given folder are found in the path string
% Keeps files and file paths in a cell array if the file names in a given folder are found in the path string
%
% Syntax: [Files] = KEEPFILESFROMFOLDER(FileList,KeepFromFolder)
%
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2 changes: 1 addition & 1 deletion octaveBandMean.m
@@ -1,5 +1,5 @@
function [ magSpect_oct, freqVec_oct ] = octaveBandMean( magSpect, freqVec, octSpace, centerFreq )
%OCTAVEBANDMEAN Given a magnitude spectrum this function will calculate the average (single, third, nth) octave band magnitude
% Given a magnitude spectrum this function will calculate the average (single, third, nth) octave band magnitude
%
% Syntax: [ MAGSPECT_OCT, FREQVEC_OCT ] = OCTAVEBANDMEAN( MAGSPECT, FREQVEC, OCTSPACE, CENTERFREQ )
%
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2 changes: 1 addition & 1 deletion pesq2.m
@@ -1,5 +1,5 @@
function [pesq_val]= pesq2(ref_sig, alt_sig, fs)
%PESQ objective speech quality measure
% Objective speech quality measure
% ----------------------------------------------------------------------
% PESQ objective speech quality measure
%
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2 changes: 1 addition & 1 deletion pesq3.m
@@ -1,5 +1,5 @@
function [ res ] = pesq3( reference_sig, degraded_sig, Fs, fileNum )
%PESQ3 A wrapper for the objective Perceptual Evaluation of Speech Quality measure
% A wrapper for the objective Perceptual Evaluation of Speech Quality measure
%
% Syntax: [ res ] = pesq3( reference_sig, degraded_sig, Fs, fileNum )
%
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2 changes: 1 addition & 1 deletion pesq_mex_vec.m
@@ -1,5 +1,5 @@
function [ res ] = pesq_mex_vec( reference_sig, degraded_sig, Fs )
%PESQ_MEX_VEC Accepts vectors for a mex compiled version of the objective Perceptual Evaluation of Speech Quality measure
% Accepts vectors for a mex compiled version of the objective Perceptual Evaluation of Speech Quality measure
%
% Syntax: [ res ] = pesq_mex_vec( reference_sig, degraded_sig, Fs )
%
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2 changes: 1 addition & 1 deletion printHyperlink.m
@@ -1,5 +1,5 @@
function printHyperlink( URL, OptionalText )
%PRINTHYPERLINK Prints a hyperlink to the command window
% Prints a hyperlink to the command window
%
% Syntax: PRINTHYPERLINK( URL, OPTIONALTEXT)
%
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2 changes: 1 addition & 1 deletion shapeSpectrum.m
@@ -1,5 +1,5 @@
function [ y_shaped ] = shapeSpectrum( y, spectrum, freqs, fs )
%SHAPESPECTRUM This function will shape an input signal to the given spectrum (simple, unregulated spectral shaping)
% This function will shape an input signal to the given spectrum (simple, unregulated spectral shaping)
%
% Syntax: [ y_shaped ] = shapeSpectrum( y, fs, spectrum )
%
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2 changes: 1 addition & 1 deletion showTimeToCompletion.m
@@ -1,5 +1,5 @@
function [ num_curr_char, history_ ] = showTimeToCompletion( percent_complete, num_prev_char, history_ )
%SHOWTIMETOCOMPLETION Prints the time to completion and expected finish of a looped simulation based on linear extrapolation.
% Prints the time to completion and expected finish of a looped simulation based on linear extrapolation.
%
% Syntax: [ num_curr_char ] = showTimeToCompletion( percent_complete, num_prev_char )
% Note that before using this function in a loop the in-built MATLAB
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