├── src ├── speech │ ├── eval1.wav │ └── eval1_echo100.wav ├── test.py └── sti.py ├── TODO ├── README └── COPYING /src/speech/eval1.wav: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmpolom/sti-wav/HEAD/src/speech/eval1.wav -------------------------------------------------------------------------------- /src/speech/eval1_echo100.wav: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmpolom/sti-wav/HEAD/src/speech/eval1_echo100.wav -------------------------------------------------------------------------------- /TODO: -------------------------------------------------------------------------------- 1 | * Python setup and install script 2 | * Develop some simple test cases 3 | * Implement unit tests 4 | * Profit. 5 | -------------------------------------------------------------------------------- /src/test.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python 2 | 3 | """ 4 | Speech Transmission Index (STI) test script 5 | 6 | Copyright (C) 2011 Jon Polom 7 | Licensed under the GNU General Public License 8 | """ 9 | 10 | from datetime import date 11 | from sti import stiFromAudio, readwav 12 | 13 | __author__ = "Jonathan Polom " 14 | __date__ = date(2011, 04, 22) 15 | __version__ = "0.5" 16 | 17 | def testSTI(): 18 | # read audio 19 | refAudio, refRate = readwav('speech/eval1.wav') 20 | degrAudio, degrRate = readwav('speech/eval1_echo100.wav') 21 | 22 | # calculate the STI. Visually verify console output. 23 | stis = stiFromAudio(refAudio, degrAudio, refRate, name='eval1.wav') 24 | 25 | print "Test Result:", 26 | 27 | # test result 28 | if abs(stis - 0.63) < 0.002: 29 | print "OK" 30 | return 0 31 | else: 32 | print "FAILED" 33 | return 1 34 | 35 | if __name__ == '__main__': 36 | testSTI() 37 | -------------------------------------------------------------------------------- /README: -------------------------------------------------------------------------------- 1 | sti.py : Speech Transmission Index (STI) from speech waveforms 2 | 3 | Overview 4 | -------- 5 | sti.py provides a library of functions used to calculate the speech 6 | transmission index (STI) from real speech waveforms. The speech trans- 7 | mission index provides an index measure of speech intelligibility, useful 8 | for evaluating transmission channel or codec suitability to carrying speech 9 | audio. The method used by sti.py was described first by Payton and Braida 10 | in 1999, and is an adaptation of the original STI method developed by 11 | Houtgast and Steeneken in 1985. Refer to those publications for further 12 | technical information on the index itself or the calculation approach. 13 | 14 | SOFTWARE DEPENDENCIES 15 | --------------------- 16 | matplotlib 17 | Numpy 18 | Scipy, release version 0.8 or greater 19 | 20 | INSTALLATION 21 | ------------ 22 | No installation is required OR AVAILABLE at this time. The only method of 23 | running the program currently is by placing the 'sti.py' file into a python 24 | project's source directory or including it in your module search path. 25 | 26 | Usage 27 | ----- 28 | sti.py provides library functions for calculating the speech transmission 29 | index. At this time no command line interface or GUI utility is available 30 | for accessing the functions. See the 'test.py' script contained in the 31 | source code directory for a brief example of calculating the STI from 32 | original and distorted raw audio samples. 33 | 34 | Authors 35 | ------- 36 | Jonathan Polom 37 | 38 | Date 39 | ---- 40 | 22 April 2011 41 | 42 | Version 43 | ------- 44 | 0.5 45 | 46 | LICENSE 47 | ------- 48 | See 'COPYING' for the details of the GNU General Public License 49 | Copyright (C) 2011 Jonathan Polom 50 | -------------------------------------------------------------------------------- /src/sti.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/python 2 | 3 | """ 4 | Speech Transmission Index (STI) from speech waveforms (real speech) 5 | 6 | Copyright (C) 2011 Jon Polom 7 | Licensed under the GNU General Public License 8 | """ 9 | 10 | from datetime import date, datetime 11 | from matplotlib.mlab import cohere,psd 12 | from numpy import append,array,clip,log10,nonzero,ones,power,reshape 13 | from numpy import searchsorted,shape,sqrt,sum,vstack,zeros 14 | from numpy.ma import masked_array 15 | from scipy.io import wavfile 16 | from scipy.signal import butter,firwin,decimate,lfilter 17 | from sys import stdout 18 | from warnings import catch_warnings,simplefilter 19 | 20 | __author__ = "Jonathan Polom " 21 | __date__ = date(2011, 04, 22) 22 | __version__ = "0.5" 23 | 24 | def thirdOctaves(minFreq, maxFreq): 25 | """ 26 | Calculates a list of frequencies spaced 1/3 octave apart in hertz 27 | between minFreq and maxFreq 28 | 29 | Input 30 | ----- 31 | * minFreq : float or int 32 | 33 | Must be non-zero and non-negative 34 | 35 | * maxFreq : float or int 36 | 37 | Must be non-zero and non-negative 38 | 39 | Output 40 | ------ 41 | * freqs : ndarray 42 | """ 43 | 44 | if minFreq <= 0 or maxFreq <= 0: 45 | raise ValueError("minFreq and maxFreq must be non-zero and non-negative") 46 | else: 47 | maxFreq = float(maxFreq) 48 | 49 | f = float(minFreq) 50 | freqs = array([f]) 51 | 52 | while f < maxFreq: 53 | f = f * 10**0.1 54 | freqs = append(freqs, f) 55 | 56 | return freqs 57 | 58 | def fftWindowSize(freqRes, hz): 59 | """ 60 | Calculate power of 2 window length for FFT to achieve specified frequency 61 | resolution. Useful for power spectra and coherence calculations. 62 | 63 | Input 64 | ----- 65 | * freqRes : float 66 | 67 | Desired frequency resolution in hertz 68 | 69 | * hz : int 70 | 71 | Sample rate, in hertz, of signal undergoing FFT 72 | 73 | Output 74 | ------ 75 | * window : int 76 | """ 77 | 78 | freqRes = float(freqRes) # make sure frequency res is a float 79 | pwr = 1 # initial power of 2 to try 80 | res = hz / float(2**pwr) # calculate frequency resolution 81 | 82 | while res > freqRes: 83 | pwr += 1 84 | res = hz / float(2**pwr) 85 | 86 | return 2**pwr 87 | 88 | def downsampleBands(audio, hz, downsampleFactor): 89 | """ 90 | Downsample audio by integer factor 91 | 92 | Input 93 | ----- 94 | * audio : array-like 95 | 96 | Array of original audio samples 97 | 98 | * hz : float or int 99 | 100 | Original audio sample rate in hertz 101 | 102 | * downsampleFactor : int 103 | 104 | Factor to downsample audio by, if desired 105 | 106 | Output 107 | ------ 108 | * dsAudio : ndarray 109 | 110 | Downsampled audio array 111 | 112 | * hz : int 113 | 114 | Downsampled audio sample rate in hertz 115 | """ 116 | 117 | # calculate downsampled audio rate in hertz 118 | downsampleFactor = int(downsampleFactor) # factor must be integer 119 | hz = int(hz / downsampleFactor) 120 | 121 | for band in audio: 122 | ds = decimate(band, downsampleFactor, ftype='fir') 123 | 124 | try: 125 | dsAudio = append(dsAudio, ds) 126 | except: 127 | dsAudio = ds 128 | 129 | return dsAudio, hz 130 | 131 | def octaveBandFilter(audio, hz, 132 | octaveBands=[125, 250, 500, 1000, 2000, 4000, 8000], 133 | butterOrd=6, hammingTime=16.6): 134 | 135 | """ 136 | Octave band filter raw audio. The audio is filtered through butterworth 137 | filters of order 6 (by default), squared to obtain the envelope and finally 138 | low-pass filtered using a 'hammingTime' length Hamming filter at 25 Hz. 139 | 140 | Input 141 | ----- 142 | * audio : array-like 143 | 144 | Array of raw audio samples 145 | 146 | * hz : float or int 147 | 148 | Audio sample rate in hertz 149 | 150 | * octaveBands : array-like 151 | 152 | list or array of octave band center frequencies 153 | 154 | * butterOrd : int 155 | 156 | butterworth filter order 157 | 158 | * hammingTime : float or int 159 | 160 | Hamming window length, in milliseconds relative to audio sample rate 161 | 162 | Output 163 | ------ 164 | * octaveBandAudio : ndarray 165 | 166 | Octave band filtered audio 167 | 168 | * hz : float or int 169 | 170 | Filtered audio sample rate 171 | """ 172 | 173 | print "Butterworth filter order:",butterOrd 174 | print "Hamming filter length: ",hammingTime,"milliseconds" 175 | print "Audio sample rate: ",hz 176 | 177 | # calculate the nyquist frequency 178 | nyquist = hz * 0.5 179 | 180 | # length of Hamming window for FIR low-pass at 25 Hz 181 | hammingLength = (hammingTime / 1000.0) * hz 182 | 183 | # process each octave band 184 | for f in octaveBands: 185 | bands = str(octaveBands[:octaveBands.index(f) + 1]).strip('[]') 186 | statusStr = "Octave band filtering audio at: " + bands 187 | unitStr = "Hz ".rjust(80 - len(statusStr)) 188 | stdout.write(statusStr) 189 | stdout.write(unitStr) 190 | stdout.write('\r') 191 | stdout.flush() 192 | 193 | # filter the output at the octave band f 194 | f1 = f / sqrt(2) 195 | f2 = f * sqrt(2) 196 | 197 | # for some odd reason the band-pass butterworth doesn't work right 198 | # when the filter order is high (above 3). likely a SciPy issue? 199 | # also, butter likes to complain about possibly useless results when 200 | # calculating filter coefficients for high order (above 4) low-pass 201 | # filters with relatively low knee frequencies (relative to nyquist F). 202 | # perhaps I just don't know how digital butterworth filters work and 203 | # their limitations but I think this is odd. 204 | # the issue described here will be sent to their mailing list 205 | if f < max(octaveBands): 206 | with catch_warnings(): # suppress the spurious warnings given 207 | simplefilter('ignore') # under certain conditions 208 | b1,a1 = butter(butterOrd, f1/nyquist, btype='high') 209 | b2,a2 = butter(butterOrd, f2/nyquist, btype='low') 210 | 211 | filtOut = lfilter(b1, a1, audio) # high-pass raw audio at f1 212 | filtOut = lfilter(b2, a2, filtOut) # low-pass after high-pass at f1 213 | else: 214 | with catch_warnings(): 215 | simplefilter('ignore') 216 | b1,a1 = butter(butterOrd, f/nyquist, btype='high') 217 | filtOut = lfilter(b1, a1, audio) 218 | 219 | filtOut = array(filtOut)**2 220 | b = firwin(hammingLength, 25.0, nyq=nyquist) 221 | filtOut = lfilter(b, 1, filtOut) 222 | filtOut = filtOut * -1.0 223 | 224 | # stack-up octave band filtered audio 225 | try: 226 | octaveBandAudio = vstack((octaveBandAudio, filtOut)) 227 | except: 228 | octaveBandAudio = filtOut 229 | 230 | print 231 | return octaveBandAudio 232 | 233 | def octaveBandSpectra(filteredAudioBands, hz, fftRes=0.06): 234 | """ 235 | Calculate octave band power spectras 236 | 237 | Input 238 | ----- 239 | * filteredAudioBands : array-like 240 | 241 | Octave band filtered audio 242 | 243 | * hz : float or int 244 | 245 | Audio sample rate in hertz. Must be the same for clean and dirty audio 246 | 247 | * fftRes : float or int 248 | 249 | Desired FFT frequency resolution 250 | 251 | Output 252 | ------ 253 | * spectras : ndarray 254 | 255 | Power spectra values 256 | 257 | * fftfreqs : ndarray 258 | 259 | Frequencies for FFT points 260 | """ 261 | 262 | # FFT window size for PSD calculation: 32768 for ~0.06 Hz res at 2 kHz 263 | psdWindow = fftWindowSize(fftRes, hz) 264 | 265 | print "Calculating octave band power spectras", 266 | print "(FFT length:",psdWindow,"samples)" 267 | 268 | for band in filteredAudioBands: 269 | spectra, freqs = psd(band, NFFT=psdWindow, Fs=hz) 270 | spectra = reshape(spectra, len(freqs)) # change to row vector 271 | spectra = spectra / max(spectra) # scale to [0,1] 272 | 273 | # stack-up octave band spectras 274 | try: 275 | spectras = vstack((spectras, spectra)) 276 | fftfreqs = vstack((fftfreqs, freqs)) 277 | except: 278 | spectras = spectra 279 | fftfreqs = freqs 280 | 281 | return spectras, fftfreqs 282 | 283 | def octaveBandCoherence(degrAudioBands, refAudioBands, 284 | hz, fftRes=0.122): 285 | """ 286 | Calculate coherence between clean and degraded octave band audio 287 | 288 | Input 289 | ----- 290 | * degrAudioBands : array-like 291 | 292 | Degraded octave band audio 293 | 294 | * refAudioBands : array-like 295 | 296 | Reference (clean) octave band audio 297 | 298 | * hz : float or int 299 | 300 | Audio sample rate. Must be common between clean and dirty audio 301 | 302 | * fftRes : float or int 303 | 304 | Desired FFT frequency resolution 305 | 306 | Output 307 | ------ 308 | * coherences : ndarray 309 | 310 | Coherence values 311 | 312 | * fftfreqs : ndarray 313 | 314 | Frequencies for FFT points 315 | """ 316 | 317 | # FFT window size for PSD calculation: 32768 for ~0.06 Hz res at 2 kHz 318 | # Beware that 'cohere' isn't as forgiving as 'psd' with FFT lengths 319 | # larger than half the length of the signal 320 | psdWindow = fftWindowSize(fftRes, hz) 321 | 322 | print "Calculating degraded and reference audio coherence", 323 | print "(FFT length:",psdWindow,"samples)" 324 | 325 | for i,band in enumerate(degrAudioBands): 326 | with catch_warnings(): # catch and ignore spurious warnings 327 | simplefilter('ignore') # due to some irrelevant divide by 0's 328 | coherence, freqs = cohere(band, refAudioBands[i], 329 | NFFT=psdWindow, Fs=hz) 330 | 331 | # stack-up octave band spectras 332 | try: 333 | coherences = vstack((coherences, coherence)) 334 | fftfreqs = vstack((fftfreqs, freqs)) 335 | except: 336 | coherences = coherence 337 | fftfreqs = freqs 338 | 339 | return coherences, fftfreqs 340 | 341 | def thirdOctaveRootSum(spectras, fftfreqs, minFreq=0.25, maxFreq=25.0): 342 | """ 343 | Calculates square root of sum of spectra over 1/3 octave bands 344 | 345 | Input 346 | ----- 347 | * spectras : array-like 348 | 349 | Array or list of octave band spectras 350 | 351 | * fftfreqs : array-like 352 | 353 | Array or list of octave band FFT frequencies 354 | 355 | * minFreq : float 356 | 357 | Min frequency in 1/3 octave bands 358 | 359 | * maxFreq : float 360 | 361 | Max frequency in 1/3 octave bands 362 | 363 | Output 364 | ------ 365 | * thirdOctaveRootSums : ndarray 366 | 367 | Square root of spectra sums over 1/3 octave intervals 368 | """ 369 | 370 | print "Calculating 1/3 octave square-rooted sums from", 371 | print minFreq,"to",maxFreq,"Hz" 372 | 373 | thirdOctaveBands = thirdOctaves(minFreq, maxFreq) 374 | 375 | # loop over the spectras contained in 'spectras' and calculate 1/3 oct MTF 376 | for i,spectra in enumerate(spectras): 377 | freqs = fftfreqs[i] # get fft frequencies for spectra 378 | 379 | # calculate the third octave sums 380 | for f13 in thirdOctaveBands: 381 | f131 = f13 / power(2, 1.0/6.0) # band start 382 | f132 = f13 * power(2, 1.0/6.0) # band end 383 | 384 | li = searchsorted(freqs, f131) 385 | ui = searchsorted(freqs, f132) + 1 386 | 387 | s = sum(spectra[li:ui]) # sum the spectral components in band 388 | s = sqrt(s) # take square root of summed components 389 | 390 | try: 391 | sums = append(sums, s) 392 | except: 393 | sums = array([s]) 394 | 395 | # stack-up third octave modulation transfer functions 396 | try: 397 | thirdOctaveSums = vstack((thirdOctaveSums, sums)) 398 | except: 399 | thirdOctaveSums = sums 400 | 401 | # remove temp 'sum' and 'counts' variables for next octave band 402 | del(sums) 403 | 404 | return thirdOctaveSums 405 | 406 | def thirdOctaveRMS(spectras, fftfreqs, minFreq=0.25, maxFreq=25.0): 407 | """ 408 | Calculates RMS value of spectra over 1/3 octave bands 409 | 410 | Input 411 | ----- 412 | * spectras : array-like 413 | 414 | Array or list of octave band spectras 415 | 416 | * fftfreqs : array-like 417 | 418 | Array or list of octave band FFT frequencies 419 | 420 | * minFreq : float 421 | 422 | Min frequency in 1/3 octave bands 423 | 424 | * maxFreq : float 425 | 426 | Max frequency in 1/3 octave bands 427 | 428 | Output 429 | ------ 430 | * thirdOctaveRMSValues : ndarray 431 | 432 | RMS value of spectra over 1/3 octave intervals 433 | """ 434 | 435 | print "Calculating 1/3 octave RMS values from", 436 | print minFreq,"to",maxFreq,"Hz" 437 | 438 | thirdOctaveBands = thirdOctaves(minFreq, maxFreq) 439 | 440 | # loop over the spectras contained in 'spectras' and calculate 1/3 oct MTF 441 | for i,spectra in enumerate(spectras): 442 | freqs = fftfreqs[i] # get fft frequencies for spectra 443 | 444 | # calculate the third octave sums 445 | for f13 in thirdOctaveBands: 446 | f131 = f13 / power(2, 1.0/6.0) # band start 447 | f132 = f13 * power(2, 1.0/6.0) # band end 448 | 449 | li = searchsorted(freqs, f131) 450 | ui = searchsorted(freqs, f132) + 1 451 | 452 | s = sum(spectra[li:ui]**2) # sum the spectral components in band 453 | s = s / len(spectra[li:ui]) # divide by length of sum 454 | s = sqrt(s) # square root 455 | 456 | try: 457 | sums = append(sums, s) 458 | except: 459 | sums = array([s]) 460 | 461 | # stack-up third octave modulation transfer functions 462 | try: 463 | thirdOctaveRMSValues = vstack((thirdOctaveRMSValues, sums)) 464 | except: 465 | thirdOctaveRMSValues = sums 466 | 467 | # remove temp 'sum' and 'counts' variables for next octave band 468 | del(sums) 469 | 470 | return thirdOctaveRMSValues 471 | 472 | def sti(modulations, coherences, minCoherence=0.8): 473 | """ 474 | Calculate the speech transmission index from third octave modulation 475 | indices. The indices are truncated after coherence between clean and dirty 476 | audio falls below 'minCoherence' or 0.8, by default. 477 | 478 | Input 479 | ----- 480 | * modulations : array-like 481 | 482 | Modulation indices spaced at 1/3 octaves within each octave band 483 | 484 | * coherences : array-like 485 | 486 | Coherence between clean and dirty octave band filtered audio 487 | 488 | * minCoherence : float 489 | 490 | The minimum coherence to include a mod index in the STI computation 491 | 492 | Output 493 | ------ 494 | * index : float 495 | 496 | The speech transmission index (STI) 497 | """ 498 | 499 | # create masking array of zeroes 500 | snrMask = zeros(modulations.shape, dtype=int) 501 | 502 | # sort through coherence array and mask corresponding SNRs where coherence 503 | # values fall below 'minCoherence' (0.8 in most cases and by default) 504 | for i,band in enumerate(coherences): 505 | lessThanMin = nonzero(band < minCoherence)[0] 506 | if len(lessThanMin) >= 1: 507 | discardAfter = min(lessThanMin) 508 | snrMask[i][discardAfter:] = ones((len(snrMask[i][discardAfter:]))) 509 | 510 | modulations = clip(modulations, 0, 0.99) # clip to [0, 0.99] (max: ~1) 511 | snr = 10*log10(modulations/(1 - modulations)) # estimate SNR 512 | snr = clip(snr, -15, 15) # clip to [-15,15] 513 | snr = masked_array(snr, mask=snrMask) # exclude values from sum 514 | snrCounts = (snr / snr).sum(axis=1) # count SNRs 515 | snrCounts = snrCounts.data # remove masking 516 | octaveBandSNR = snr.sum(axis=1) / snrCounts # calc average SNR 517 | alpha = 7 * (snrCounts / snrCounts.sum()) # calc alpha weight 518 | 519 | # octave band weighting factors, Steeneken and Houtgast (1985) 520 | w = [0.129, 0.143, 0.114, 0.114, 0.186, 0.171, 0.143] 521 | 522 | # calculate the STI measure 523 | snrp = alpha * w * octaveBandSNR 524 | snrp = snrp.sum() 525 | index = (snrp + 15) / 30.0 526 | 527 | print "Speech Transmission Index (STI):",index 528 | return index 529 | 530 | def stiFromAudio(reference, degraded, hz, calcref=False, downsample=None, 531 | name="unnamed"): 532 | """ 533 | Calculate the speech transmission index (STI) from clean and dirty 534 | (ie: distorted) audio samples. The clean and dirty audio samples must have 535 | a common sample rate for successful use of this function. 536 | 537 | Input 538 | ----- 539 | * reference : array-like 540 | 541 | Clean reference audio sample as an array of floating-point values 542 | 543 | * degraded : array-like 544 | 545 | Degraded audio sample as an array, or array of arrays for multiple 546 | samples, of floating-point values 547 | 548 | * hz : int 549 | 550 | Audio sample rate in hertz 551 | 552 | * calcref : boolean 553 | 554 | Calculate STI for reference signal alone 555 | 556 | * downsample : int or None 557 | 558 | Downsampling integer factor 559 | 560 | * name : string 561 | 562 | Name of sample set, for output tracking in larger runs 563 | 564 | Output 565 | ------ 566 | * sti : array-like or float 567 | 568 | The calculated speech transmission index (STI) value(s) 569 | """ 570 | 571 | # put single sample degraded array into another array so the loop works 572 | if type(degraded) is not type([]): 573 | degraded = [degraded] 574 | 575 | print "-"*80 576 | print "Speech Transmission Index (STI) from speech waveforms".center(80) 577 | print "-"*80 578 | print 579 | print "Sample set: ",name 580 | print "Number of samples: ",len(degraded) 581 | print "Date/time: ",datetime.now().isoformat() 582 | print "Calculate reference STI:", 583 | if calcref: 584 | print "yes" 585 | else: 586 | print "no" 587 | print 588 | print " Reference Speech ".center(80,'*') 589 | 590 | refOctaveBands = octaveBandFilter(reference, hz) 591 | refRate = hz 592 | 593 | # downsampling, if desired 594 | if type(downsample) is type(1): 595 | refOctaveBands, refRate = downsampleBands(refOctaveBands, refRate, 596 | downsample) 597 | 598 | # calculate STI for reference sample, if boolean set 599 | if calcref: 600 | # STI calc procedure 601 | spectras, sfreqs = octaveBandSpectra(refOctaveBands, refRate) 602 | coherences, cfreqs = octaveBandCoherence(refOctaveBands, refOctaveBands, 603 | refRate) 604 | thirdOctaveMTF = thirdOctaveRootSum(spectras, sfreqs) 605 | thirdOctaveCoherences = thirdOctaveRMS(coherences, cfreqs) 606 | 607 | # add to interim array for MTFs and coherences 608 | try: 609 | thirdOctaveTemps.append([thirdOctaveMTF, thirdOctaveCoherences]) 610 | except: 611 | thirdOctaveTemps = [[thirdOctaveMTF, thirdOctaveCoherences]] 612 | 613 | print 614 | 615 | # loop over degraded audio samples and calculate STIs 616 | for j,sample in enumerate(degraded): 617 | print " Degraded Speech: Sample {0} ".format(j + 1).center(80,'*') 618 | degrOctaveBands = octaveBandFilter(sample, hz) 619 | degrRate = hz 620 | 621 | # downsampling, if desired 622 | if type(downsample) is type(1): 623 | degrOctaveBands, degrRate = downsampleBands(degrOctaveBands, 624 | degrRate, downsample) 625 | 626 | # STI calc procedure 627 | spectras, sfreqs = octaveBandSpectra(degrOctaveBands, degrRate) 628 | coherences, cfreqs = octaveBandCoherence(refOctaveBands, 629 | degrOctaveBands, refRate) 630 | thirdOctaveMTF = thirdOctaveRootSum(spectras, sfreqs) 631 | thirdOctaveCoherences = thirdOctaveRMS(coherences, cfreqs) 632 | 633 | # add to interim array for MTFs and coherences 634 | try: 635 | thirdOctaveTemps.append([thirdOctaveMTF, thirdOctaveCoherences]) 636 | except: 637 | thirdOctaveTemps = [[thirdOctaveMTF, thirdOctaveCoherences]] 638 | 639 | print 640 | 641 | # calculate the STI values 642 | print " Speech Transmission Index ".center(80,'*') 643 | for i in range(0,len(thirdOctaveTemps)): 644 | sampleSTI = sti(thirdOctaveTemps[i][0], thirdOctaveTemps[i][1]) 645 | 646 | # add to STI output array 647 | try: 648 | stiValues.append(sampleSTI) 649 | except: 650 | stiValues = [sampleSTI] 651 | 652 | # unpack single value 653 | if len(stiValues) == 1: 654 | stiValues = stiValues[0] 655 | 656 | print 657 | return stiValues 658 | 659 | def readwav(path): 660 | """ 661 | Reads Microsoft WAV format audio files, scales integer sample values and 662 | to [0,1]. Returns a tuple consisting of scaled WAV samples and sample rate 663 | in hertz. 664 | 665 | Input 666 | ----- 667 | * path : string 668 | 669 | Valid system path to file 670 | 671 | Output 672 | ------ 673 | * audio : array-like 674 | 675 | Array of scaled sampled 676 | 677 | * rate : int 678 | 679 | Audio sample rate in hertz 680 | """ 681 | wav = wavfile.read(path) 682 | 683 | rate = wav[0] 684 | audio = array(wav[1]) 685 | 686 | scale = float(max(audio)) 687 | audio = audio / scale 688 | 689 | return audio, rate 690 | -------------------------------------------------------------------------------- /COPYING: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Patents. 472 | 473 | A "contributor" is a copyright holder who authorizes use under this 474 | License of the Program or a work on which the Program is based. The 475 | work thus licensed is called the contributor's "contributor version". 476 | 477 | A contributor's "essential patent claims" are all patent claims 478 | owned or controlled by the contributor, whether already acquired or 479 | hereafter acquired, that would be infringed by some manner, permitted 480 | by this License, of making, using, or selling its contributor version, 481 | but do not include claims that would be infringed only as a 482 | consequence of further modification of the contributor version. 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You may not convey a covered 525 | work if you are a party to an arrangement with a third party that is 526 | in the business of distributing software, under which you make payment 527 | to the third party based on the extent of your activity of conveying 528 | the work, and under which the third party grants, to any of the 529 | parties who would receive the covered work from you, a discriminatory 530 | patent license (a) in connection with copies of the covered work 531 | conveyed by you (or copies made from those copies), or (b) primarily 532 | for and in connection with specific products or compilations that 533 | contain the covered work, unless you entered into that arrangement, 534 | or that patent license was granted, prior to 28 March 2007. 535 | 536 | Nothing in this License shall be construed as excluding or limiting 537 | any implied license or other defenses to infringement that may 538 | otherwise be available to you under applicable patent law. 539 | 540 | 12. No Surrender of Others' Freedom. 541 | 542 | If conditions are imposed on you (whether by court order, agreement or 543 | otherwise) that contradict the conditions of this License, they do not 544 | excuse you from the conditions of this License. If you cannot convey a 545 | covered work so as to satisfy simultaneously your obligations under this 546 | License and any other pertinent obligations, then as a consequence you may 547 | not convey it at all. For example, if you agree to terms that obligate you 548 | to collect a royalty for further conveying from those to whom you convey 549 | the Program, the only way you could satisfy both those terms and this 550 | License would be to refrain entirely from conveying the Program. 551 | 552 | 13. Use with the GNU Affero General Public License. 553 | 554 | Notwithstanding any other provision of this License, you have 555 | permission to link or combine any covered work with a work licensed 556 | under version 3 of the GNU Affero General Public License into a single 557 | combined work, and to convey the resulting work. The terms of this 558 | License will continue to apply to the part which is the covered work, 559 | but the special requirements of the GNU Affero General Public License, 560 | section 13, concerning interaction through a network will apply to the 561 | combination as such. 562 | 563 | 14. Revised Versions of this License. 564 | 565 | The Free Software Foundation may publish revised and/or new versions of 566 | the GNU General Public License from time to time. Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | --------------------------------------------------------------------------------