def __init__(self, logfile=None): """ """ sppasBase.__init__(self, logfile) self.intsint = Intsint()
def __init__(self, logfile=None): """ Constructor. @param logfile (sppasLog) is a log file utility class member. """ sppasBase.__init__(self, logfile) self.momel = Momel() self.PAS_TRAME = 10.
def __init__(self, resourcefile, logfile=None): """ Create a new sppasRepetition instance. @param resourcefile is either the lemma dictionary or the list of stop-words. Attention: the extention of the resource file name is very important: must be ".stp" for stop-words and ".lem" for lemmas (case-sensitive)! """ sppasBase.__init__(self, logfile) # Members self._use_lemmatize = True # Lemmatize the input self._use_stopwords = True # Add specific stopwords of the input self._empan = 5 # Detection length (nb of IPUs; 1=current IPU) self._alpha = 0.5 # Specific stop-words threshold coefficient self.logfile = logfile self.lemmatizer = None self.stopwords = None # Create the lemmatizer instance try: lemmafile = resourcefile.replace(".stp", ".lem") self.lemmatizer = LemmaDict(lemmafile) except Exception: self._use_lemmatize = False if (self._use_lemmatize is True and self.lemmatizer.get_size() == 0) or self._use_lemmatize is False: if logfile is not None: logfile.print_message("Lemmatization disabled.",indent=2,status=3) else: print " ... ... [ INFO ] Lemmatization disabled." self._use_lemmatize = False # Create the list of stop words (list of non-relevant words) try: stopfile = resourcefile.replace(".lem", ".stp") self.stopwords = WordsList(filename=resourcefile, nodump=True) if self.stopwords.get_size() == 0: self._use_stopwords = False except Exception: self.stopwords = WordsList() #if (self._use_stopwords is True and self.stopwords.get_size() == 0) or self._use_stopwords is False: if self._use_stopwords is False: if logfile is not None: logfile.print_message("StopWords disabled.",indent=2,status=3) else: print " ... ... [ INFO ] StopWords disabled."
def __init__(self, model, modelL1=None, logfile=None): """ Create a new sppasAlign instance. @param model (str) the acoustic model directory name of the language of the text @param modelL1 (str) the acoustic model directory name of the mother language of the speaker @param logfile (sppasLog) """ sppasBase.__init__(self, logfile) # Members: self.alignio self.fix_segmenter( model,modelL1 ) self.reset()
def __init__(self, model, logfile=None): """ Create a new sppasChunks instance. @param model (str) the acoustic model directory name of the language of the text @param modelL1 (str) the acoustic model directory name of the mother language of the speaker @param logfile (sppasLog) """ sppasBase.__init__(self, logfile) self.chunks = Chunks(model) self._options["clean"] = True # Remove temporary files self._options["silences"] = self.chunks.get_silences() self._options["anchors"] = self.chunks.get_anchors() self._options["ngram"] = self.chunks.get_ngram_init() self._options["ngrammin"] = self.chunks.get_ngram_min() self._options["windelay"] = self.chunks.get_windelay_init() self._options["windelaymin"] = self.chunks.get_windelay_min() self._options["chunksize"] = self.chunks.get_chunk_maxsize()
def __init__(self, dictfilename, mapfile=None, logfile=None): """ Constructor. @param dictfilename (str) is the pronunciation dictionary file name (HTK-ASCII format, utf8). @param mapfile (str) is the filename of a mapping table. It is used to generate new pronunciations by mapping phonemes of the dictionary. @param logfile (sppasLog) is a log file utility class member. """ sppasBase.__init__(self, logfile) # Pronunciation dictionary self.maptable = None if mapfile is not None: self.maptable = Mapping( mapfile ) self.set_dict( dictfilename ) # List of options to configure this automatic annotation self._options = {} self._options['phonunk'] = False # Phonetize missing tokens self._options['usestdtokens'] = False # Phonetize standard spelling