How to use the praatio.dataio.PointObject2D function in praatio

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github timmahrt / praatIO / praatio / View on Github external
                start = data.index('=', start)
            except ValueError:
            timeVal, start = _getNextValue(data, start)
                start = data.index('=', start)
            except ValueError:
            pointVal, start = _getNextValue(data, start)
            dataList.append([float(timeVal), float(pointVal), ])
        po = PointObject2D(dataList, objectType, minT, maxT)
        data, objectType, minT, maxT = _parseShortHeader(fn)
        dataList = data.split('\n')
        dataList = [(float(dataList[i]), float(dataList[i + 1]))
                    for i in range(0, len(dataList), 2)
                    if dataList[i].strip() != '']
        po = PointObject2D(dataList, objectType, minT, maxT)
    return po
github timmahrt / praatIO / praatio / View on Github external
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,

    utils.runPraatScript(praatEXE, scriptFN,
                         [inputWavFN, pitchFN, outputWavFN,
                          minPitch, maxPitch])
github timmahrt / ProMo / promo / View on Github external
durationParameters.append((durationParameters[-1][1] + PRAAT_TIME_DIFF,
                                   fromWavDuration, 1))

    # Create the praat script for doing duration manipulation
    for stepAmount in stepList:
        durationPointList = []
        for start, end, ratio in durationParameters:
            percentChange = 1 + (ratio - 1) * stepAmount
            durationPointList.append((start, percentChange))
            durationPointList.append((end, percentChange))
        outputPrefix = "%s_%0.3g" % (outputName, stepAmount)
        durationTierFN = join(durationTierPath,
                              "%s.DurationTier" % outputPrefix)
        outputWavFN = join(outputPath, "%s.wav" % outputPrefix)
        durationTier = dataio.PointObject2D(durationPointList, dataio.DURATION,
                                            0, fromWavDuration)
                                           outputMinPitch, outputMaxPitch)
github timmahrt / ProMo / examples / View on Github external
outputWavFN = "mary1_accented.wav"
outputPitchFN = "mary1_accented.pitch"
minPitch = 75
maxPitch = 450

if not os.path.exists(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), 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
accent.shiftAccent(-0.03)  # Recenter the plateau around the original peak
github timmahrt / ProMo / promo / View on Github external
if keepPitchRange is True:
            outputDataList = morph_sequence.morphRange(outputDataList,
        if keepAveragePitch is True:
            outputDataList = morph_sequence.morphAveragePitch(outputDataList,
        if sourcePitchDataList is not None:
        stepOutputName = "%s_%0.3g" % (outputName, stepList[i])
        pitchFNFullPath = join(pitchTierPath, "%s.PitchTier" % stepOutputName)
        outputFN = join(resynthesizedPath, "%s.wav" % stepOutputName)
        pointObj = dataio.PointObject2D(outputDataList, dataio.PITCH,
                                        0, fromDuration)

        outputTime, outputVals = zip(*outputDataList)
        mergedDataList.append((outputTime, outputVals))
        praat_scripts.resynthesizePitch(praatEXE, fromWavFN, pitchFNFullPath,
                                        outputFN, outputMinPitch,

    # 4. (Optional) Plot the generated contours
    if doPlotPitchSteps:

        fromTime, fromVals = zip(*fromPitchData)
        toTime, toVals = zip(*toPitchData)
github timmahrt / praatIO / praatio / View on Github external
def __init__(self, pointList, objectClass, minTime=0, maxTime=None):

        assert(objectClass != POINT)
        if maxTime is None:
            maxTime = max([timeV for timeV, _ in pointList])
        super(PointObject2D, self).__init__(pointList, objectClass,
                                            minTime, maxTime)