def resynthesizePitch(praatEXE,
inputWavFN,
pitchFN,
outputWavFN,
minPitch,
maxPitch,
scriptFN=None,
pointList=None):
'''
Resynthesizes the pitch in a wav file with the given pitch contour file
The pitch track to use can optionally be passed in as pointList. If
so, it will be saved as pitchFN for praat to be able to use.
'''
if scriptFN is None:
scriptFN = join(utils.scriptsPath, "resynthesize_pitch.praat")
if pointList is not None:
dur = audioio.WavQueryObj(inputWavFN).getDuration()
pointObj = dataio.PointObject2D(pointList, dataio.PITCH, 0, dur)
pointObj.save(pitchFN)
utils.runPraatScript(
praatEXE, scriptFN,
[inputWavFN, pitchFN, outputWavFN, minPitch, maxPitch])
def segment_audio(audiodir, wavdir, tgs, long2iso):
print('Segmenting %s from %s to %s'%(str([x for x in tgs.keys()]),wavdir,audiodir))
outputnames = []
for (filename,tg) in tgs.items():
entryList = tg.tierDict['seg'].entryList
entryList = [ entry for entry in entryList if not entry[2].isspace() ]
outdir = os.path.join(audiodir,filename)
os.makedirs(outdir,exist_ok=True)
inputfile = os.path.join(wavdir, filename+'.wav')
wavQObj = audioio.WavQueryObj(inputfile)
for entry in entryList:
start, stop, label = entry
if not label.isnumeric():
raise RunTimeError('TextGrid %s contains non-numeric label %s'%(filename,label))
outputname = os.path.join(outdir, '%s_%4.4d.wav'%(filename,int(label)))
frames = wavQObj.getFrames(start, stop)
wavQObj.outputModifiedWav(frames, outputname)
outputnames.append(outputname)
def deleteVowels(inputTGFN,
inputWavFN,
outputPath,
doShrink,
atZeroCrossing=True):
utils.makeDir(outputPath)
wavFN = os.path.split(inputWavFN)[1]
tgFN = os.path.split(inputTGFN)[1]
outputWavFN = join(outputPath, wavFN)
outputTGFN = join(outputPath, tgFN)
if atZeroCrossing is True:
zeroCrossingTGPath = join(outputPath, "zero_crossing_tgs")
zeroCrossingTGFN = join(zeroCrossingTGPath, tgFN)
utils.makeDir(zeroCrossingTGPath)
tg = tgio.openTextgrid(inputTGFN)
wavObj = audioio.WavQueryObj(inputWavFN)
praatio_scripts.tgBoundariesToZeroCrossings(tg, wavObj,
zeroCrossingTGFN)
else:
tg = tgio.openTextgrid(inputTGFN)
keepList = tg.tierDict["phone"].entryList
keepList = [entry for entry in keepList if not isVowel(entry[2])]
deleteList = utils.invertIntervalList(keepList, tg.maxTimestamp)
wavObj = audioio.openAudioFile(inputWavFN,
keepList=keepList,
doShrink=doShrink)
wavObj.save(outputWavFN)
shrunkTG = copy.deepcopy(tg)
for start, stop in sorted(deleteList, reverse=True):
shrunkTG = shrunkTG.eraseRegion(start, stop, doShrink=doShrink)
shrunkTG.save(outputTGFN)
from praatio import tgio
from praatio import audioio
path = join(".", "files")
outputPath = join(path, "anonymized_data")
if not os.path.exists(outputPath):
os.mkdir(outputPath)
for wavFN, tgFN in (("mary.wav", "mary.TextGrid"), ("bobby.wav",
"bobby_words.TextGrid")):
outputWavFN = join(outputPath, wavFN)
# Find the word(s) to anonymize
# (One could imagine a search for common names or identification of
# some sort of code ('section-to-anonymize') rather than what I have
# done here.
deleteList = []
tg = tgio.openTextgrid(join(path, tgFN))
deleteList.append(tg.tierDict['word'].entryList[0])
# Get only time information from entries (i.e. remove label information)
deleteList = [(start, stop) for start, stop, _ in deleteList]
# Replace segments with a sine wave
wavQObj = audioio.WavQueryObj(join(path, wavFN))
wavQObj.deleteWavSections(outputWavFN,
deleteList=deleteList,
operation="sine wave")
originalPitchFN = "mary1.pitch"
outputWavFN = "mary1_accented.wav"
outputPitchFN = "mary1_accented.pitch"
minPitch = 75
maxPitch = 450
if not os.path.exists(rootOutputPath):
os.mkdir(rootOutputPath)
# 1st - get pitch
piList = pitch_and_intensity.extractPI(join(root, wavFN),
join(rootOutputPath, pitchIntensityFN),
praatEXE, minPitch, maxPitch)
pitchList = [(timeV, pitchV) for timeV, pitchV, _ in piList]
dur = audioio.WavQueryObj(join(root, wavFN)).getDuration()
pointObj = dataio.PointObject2D(pitchList, dataio.PITCH, 0, dur)
pointObj.save(join(rootOutputPath, originalPitchFN))
# 2nd - get region to manipulate. Let's make the subject more emphatic!
tg = tgio.openTextgrid(join(root, "mary1.TextGrid"))
tier = tg.tierDict["words"]
start, stop, _ = tier.entryList[0] # Getting info for the first word
targetPitchList = [(timeV, pitchV) for timeV, pitchV in pitchList
if timeV >= start and timeV <= stop]
# 3rd - make manipulation
accent = modify_pitch_accent.PitchAccent(targetPitchList)
accent.addPlateau(0.05) # Peak is dragged out for 0.05 seconds
accent.adjustPeakHeight(60) # Plateau is raised by 60 hz
def splitAudioOnTier(wavFN, tgFN, tierName, outputPath,
outputTGFlag=False, nameStyle=None,
noPartialIntervals=False, silenceLabel=None):
'''
Outputs one subwav for each entry in the tier of a textgrid
outputTGFlag: If True, outputs paired, cropped textgrids
If is type str (a tier name), outputs a paired, cropped
textgrid with only the specified tier
nameStyle: if 'append': append interval label to output name
if 'append_no_i': append label but not interval to output name
if 'label': output name is the same as label
if None: output name plus the interval number
noPartialIntervals: if True: intervals in non-target tiers that are
not wholly contained by an interval in
the target tier will not be included in
the output textgrids
silenceLabel: the label for silent regions. If silences are unlabeled
intervals (i.e. blank) then leave this alone. If silences
are labeled using praat's "annotate >> to silences"
then this value should be "silences"
'''
if not os.path.exists(outputPath):
os.mkdir(outputPath)
if noPartialIntervals is True:
mode = 'strict'
else:
mode = 'truncated'
tg = tgio.openTextgrid(tgFN)
entryList = tg.tierDict[tierName].entryList
if silenceLabel is not None:
entryList = [entry for entry in entryList
if entry[2] != silenceLabel]
# Build the output name template
name = os.path.splitext(os.path.split(wavFN)[1])[0]
orderOfMagnitude = int(math.floor(math.log10(len(entryList))))
# We want one more zero in the output than the order of magnitude
outputTemplate = "%s_%%0%dd" % (name, orderOfMagnitude + 1)
firstWarning = True
# If we're using the 'label' namestyle for outputs, all of the
# interval labels have to be unique, or wave files with those
# labels as names, will be overwritten
if nameStyle == 'label':
wordList = [word for _, _, word in entryList]
multipleInstList = []
for word in set(wordList):
if wordList.count(word) > 1:
multipleInstList.append(word)
if len(multipleInstList) > 0:
instListTxt = "\n".join(multipleInstList)
print(("Overwriting wave files in: %s\n" +
"Intervals exist with the same name:\n%s")
% (outputPath, instListTxt))
firstWarning = False
# Output wave files
outputFNList = []
wavQObj = audioio.WavQueryObj(wavFN)
for i, entry in enumerate(entryList):
start, stop, label = entry
# Resolve output name
outputName = outputTemplate % i
if nameStyle == "append":
outputName += "_" + label
elif nameStyle == "append_no_i":
outputName = name + "_" + label
elif nameStyle == "label":
outputName = label
outputFNFullPath = join(outputPath, outputName + ".wav")
if os.path.exists(outputFNFullPath) and firstWarning:
print(("Overwriting wave files in: %s\n" +
"Files existed before or intervals exist with " +
"the same name:\n%s")
% (outputPath, outputName))
frames = wavQObj.getFrames(start, stop)
wavQObj.outputModifiedWav(frames, outputFNFullPath)
outputFNList.append((start, stop, outputName + ".wav"))
# Output the textgrid if requested
if outputTGFlag is not False:
subTG = tg.crop(start, stop, mode, True)
if isinstance(outputTGFlag, str):
for tierName in subTG.tierNameList:
if tierName != outputTGFlag:
subTG.removeTier(tierName)
subTG.save(join(outputPath, outputName + ".TextGrid"))
return outputFNList
