'graph_host': 'localhost',
'graph_port': 7474,
'graph_user': '******',
'graph_password': '******'
}
praat = r'C:\Users\michael\Documents\Praat\praatcon.exe'
reaper = r'D:\Dev\Tools\REAPER-master\reaper.exe'
speaker_info_path = r'D:\Data\VIC\SpeakerInfo.txt'
config = CorpusConfig('buckeye', **graph_db)
config.reaper_path = reaper
config.praat_path = praat
config.pitch_algorithm = 'praat'
def call_back(*args):
args = [x for x in args if isinstance(x, str)]
if args:
print(' '.join(args))
if __name__ == '__main__':
with CorpusContext(config) as g:
g.reset_acoustics()
if not 'utterance' in g.annotation_types:
g.encode_pauses('^[{<].*', call_back=call_back)
g.encode_utterances(min_pause_length=0.15, call_back=call_back)
q = q.columns(c.phone.speaker.name.column_name('speaker'),
c.phone.discourse.name.column_name('discourse'),
c.phone.id.column_name('phone_id'),
c.phone.label.column_name('phone_label'),
c.phone.begin.column_name('begin'),
c.phone.end.column_name('end'),
c.phone.following.label.column_name('following_phone'),
c.phone.previous.label.column_name('previous_phone'),
c.phone.word.label.column_name('word'),
c.phone.cog.column_name('cog'),
c.phone.peak.column_name('peak'),
c.phone.slope.column_name('slope'),
c.phone.spread.column_name('spread'))
q.to_csv(output_path_word_initial)
print("Results for sibilants written to " + output_path + " and " +
output_path_word_initial)
if __name__ == '__main__':
with ensure_local_database_running('database') as config:
conf = CorpusConfig(corpus_name, **config)
conf.pitch_source = 'praat'
# config.pitch_algorithm = 'base'
conf.formant_source = 'praat'
conf.intensity_source = 'praat'
conf.praat_path = praat_path
if reset:
loading(conf)
acoustics(conf)
analysis(conf)
