'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)