def GetPlotnikCode(line): """ Call arpabet2plotnik -> in oder to get the plotnik vowel classes """ phoneset = cmu.read_phoneset("../cmu_phoneset.txt") vowelSystem = "NorthAmerican" trans = line[30] ac = line[27] stress = line[28] phone = extractFormants.Phone() xmin = float(line[38]) xmax = float(line[39]) phone.label = ac + stress phone.xmin = xmin phone.xmax = xmax i = 0 phones = [phone] speaker = extractFormants.Speaker() code, prec_p = plotnik.cmu2plotnik_code(i, phones, trans, phoneset, speaker, vowelSystem) return code.split('.')[0]
from shorta import is_tense # setup for testing old system from cmu import read_phoneset from extractFormants import Phone from plotnik_old import phila_system, cmu2plotnik_code phoneset = read_phoneset('../cmu_phoneset.txt') def is_tense_old(word, pron): try: i = pron.index("AE1") except ValueError: return "irrelevant" phones = [] for phone in pron: myphone = Phone() myphone.label = phone phones.append(myphone) trans = word (code, prec_p) = cmu2plotnik_code(i, phones, trans, phoneset, None, "PHILA") fm = code.split(".")[1][0] fp = code.split(".")[1][1] fv = code.split(".")[1][2] ps = code.split(".")[1][3] fs = code.split(".")[1][4] pc = "3" pcode = phila_system(i, phones, trans, fm, fp, fv, ps, fs, pc, phoneset) if pcode == "33": return True
case = options['case'] outputFormat = options['outputFormat'] outputHeader = options['outputHeader'] formantPredictionMethod = options['formantPredictionMethod'] measurementPointMethod = options['measurementPointMethod'] speechSoftware = options['speechSoftware'] nFormants = int(options['nFormants']) maxFormant = int(options['maxFormant']) removeStopWords = options['removeStopWords'] measureUnstressed = options['measureUnstressed'] minVowelDuration = float(options['minVowelDuration']) windowSize = float(options['windowSize']) preEmphasis = float(options['preEmphasis']) multipleFiles = options['multipleFiles'] phoneset = cmu.read_phoneset(phonesetFile) # make sure the specified speech analysis program is in our path speechSoftware = checkSpeechSoftware(speechSoftware) # determine what program we'll use to extract portions of the audio file soundEditor = getSoundEditor() # if we're using the Mahalanobis distance metric for vowel formant prediction, we need to load files with the mean and covariance values if formantPredictionMethod == 'mahalanobis': means = loadMeans(meansFile) covs = loadCovs(covsFile) # put the list of stop words in upper or lower case to match the word transcriptions newStopWords = [] for w in stopWords:
from shorta import is_tense # setup for testing old system from cmu import read_phoneset from extractFormants import Phone from plotnik_old import phila_system, cmu2plotnik_code phoneset = read_phoneset('../cmu_phoneset.txt') def is_tense_old(word, pron): try: i = pron.index("AE1") except ValueError: return "irrelevant" phones = [] for phone in pron: myphone = Phone() myphone.label = phone phones.append(myphone) trans = word (code, prec_p) = cmu2plotnik_code(i, phones, trans, phoneset, None, "PHILA") fm = code.split(".")[1][0] fp = code.split(".")[1][1] fv = code.split(".")[1][2] ps = code.split(".")[1][3] fs = code.split(".")[1][4] pc = "3" pcode = phila_system(i, phones, trans, fm, fp, fv, ps, fs, pc, phoneset)