def test_merge(self):
dacn = DialogueActConfusionNetwork()
dacn.add(0.05, DialogueActItem(dai='inform(food=chinese)'))
dacn.add(0.9, DialogueActItem(dai='inform(food=czech)'))
dacn.add(0.00005, DialogueActItem(dai='inform(food=russian)'))
dacn.merge(dacn, combine='max')
# Russian food should be pruned.
dacn.sort().prune()
self.assertTrue(not DialogueActItem(dai='inform(food=russian)') in dacn)
def test_merge(self):
dacn = DialogueActConfusionNetwork()
dacn.add(0.05, DialogueActItem(dai='inform(food=chinese)'))
dacn.add(0.9, DialogueActItem(dai='inform(food=czech)'))
dacn.add(0.00005, DialogueActItem(dai='inform(food=russian)'))
dacn.merge(dacn, combine='max')
# Russian food should be pruned.
dacn.sort().prune()
self.assertTrue(not DialogueActItem(
dai='inform(food=russian)') in dacn)
def parse_1_best(self, obs, verbose=False, *args, **kwargs):
"""Parse an utterance into a dialogue act.
:rtype DialogueActConfusionNetwork
"""
utterance = obs['utt']
if isinstance(utterance, UtteranceHyp):
# Parse just the utterance and ignore the confidence score.
utterance = utterance.utterance
if verbose:
print 'Parsing utterance "{utt}".'.format(utt=utterance)
res_cn = DialogueActConfusionNetwork()
dict_da = self.utt2da.get(unicode(utterance), None)
if dict_da:
for dai in DialogueAct(dict_da):
res_cn.add(1.0, dai)
return res_cn
utterance = self.preprocessing.normalise_utterance(utterance)
abutterance, category_labels = self.abstract_utterance(utterance)
if verbose:
print 'After preprocessing: "{utt}".'.format(utt=abutterance)
print category_labels
self.parse_non_speech_events(utterance, res_cn)
utterance = utterance.replace_all(['_noise_'], '').replace_all(
['_laugh_'], '').replace_all(['_ehm_hmm_'],
'').replace_all(['_inhale_'], '')
abutterance = abutterance.replace_all(['_noise_'], '').replace_all(
['_laugh_'], '').replace_all(['_ehm_hmm_'],
'').replace_all(['_inhale_'], '')
abutterance = self.handle_false_abstractions(abutterance)
category_labels.add('CITY')
category_labels.add('VEHICLE')
category_labels.add('NUMBER')
if len(res_cn) == 0:
if 'STOP' in category_labels:
self.parse_stop(abutterance, res_cn)
if 'CITY' in category_labels:
self.parse_city(abutterance, res_cn)
if 'NUMBER' in category_labels:
self.parse_number(abutterance)
if any([word.startswith("TIME") for word in abutterance]):
category_labels.add('TIME')
if 'TIME' in category_labels:
self.parse_time(abutterance, res_cn)
if 'DATE_REL' in category_labels:
self.parse_date_rel(abutterance, res_cn)
if 'AMPM' in category_labels:
self.parse_ampm(abutterance, res_cn)
if 'VEHICLE' in category_labels:
self.parse_vehicle(abutterance, res_cn)
if 'TASK' in category_labels:
self.parse_task(abutterance, res_cn)
self.parse_meta(utterance, res_cn)
res_cn.merge()
return res_cn
def parse_1_best(self, obs, verbose=False, *args, **kwargs):
"""Parse an utterance into a dialogue act.
:rtype DialogueActConfusionNetwork
"""
utterance = obs['utt']
if isinstance(utterance, UtteranceHyp):
# Parse just the utterance and ignore the confidence score.
utterance = utterance.utterance
if verbose:
print 'Parsing utterance "{utt}".'.format(utt=utterance)
res_cn = DialogueActConfusionNetwork()
dict_da = self.utt2da.get(unicode(utterance), None)
if dict_da:
for dai in DialogueAct(dict_da):
res_cn.add(1.0, dai)
return res_cn
utterance = self.preprocessing.normalise_utterance(utterance)
abutterance, category_labels = self.abstract_utterance(utterance)
if verbose:
print 'After preprocessing: "{utt}".'.format(utt=abutterance)
print category_labels
self.parse_non_speech_events(utterance, res_cn)
utterance = utterance.replace_all(['_noise_'], '').replace_all(['_laugh_'], '').replace_all(['_ehm_hmm_'], '').replace_all(['_inhale_'], '')
abutterance = abutterance.replace_all(['_noise_'], '').replace_all(['_laugh_'], '').replace_all(['_ehm_hmm_'], '').replace_all(['_inhale_'], '')
abutterance = self.handle_false_abstractions(abutterance)
category_labels.add('CITY')
category_labels.add('VEHICLE')
category_labels.add('NUMBER')
if len(res_cn) == 0:
if 'STOP' in category_labels:
self.parse_stop(abutterance, res_cn)
if 'CITY' in category_labels:
self.parse_city(abutterance, res_cn)
if 'NUMBER' in category_labels:
self.parse_number(abutterance)
if any([word.startswith("TIME") for word in abutterance]):
category_labels.add('TIME')
if 'TIME' in category_labels:
self.parse_time(abutterance, res_cn)
if 'DATE_REL' in category_labels:
self.parse_date_rel(abutterance, res_cn)
if 'AMPM' in category_labels:
self.parse_ampm(abutterance, res_cn)
if 'VEHICLE' in category_labels:
self.parse_vehicle(abutterance, res_cn)
if 'TASK' in category_labels:
self.parse_task(abutterance, res_cn)
self.parse_meta(utterance, res_cn)
res_cn.merge()
return res_cn
def test_session_logger(self):
cfg = Config.load_configs(config=CONFIG_DICT, use_default=False)
sl = SessionLogger()
# test 3 calls at once
for i in range(3):
sess_dir = "./%d" % i
if not os.path.isdir(sess_dir):
os.mkdir(sess_dir)
sl.session_start(sess_dir)
sl.config('config = ' + unicode(cfg))
sl.header(cfg['Logging']["system_name"], cfg['Logging']["version"])
sl.input_source("voip")
sl.dialogue_rec_start(None, "both_complete_dialogue.wav")
sl.dialogue_rec_start("system", "system_complete_dialogue.wav")
sl.dialogue_rec_start("user", "user_complete_dialogue.wav")
sl.dialogue_rec_end("both_complete_dialogue.wav")
sl.dialogue_rec_end("system_complete_dialogue.wav")
sl.dialogue_rec_end("user_complete_dialogue.wav")
sl.turn("system")
sl.dialogue_act("system", "hello()")
sl.text("system", "Hello.")
sl.rec_start("system", "system1.wav")
sl.rec_end("system1.wav")
sl.turn("user")
sl.rec_start("user", "user1.wav")
sl.rec_end("user1.wav")
A1, A2, A3 = 0.90, 0.05, 0.05
B1, B2, B3 = 0.70, 0.20, 0.10
C1, C2, C3 = 0.80, 0.10, 0.10
asr_confnet = UtteranceConfusionNetwork()
asr_confnet.add([[A1, "want"], [A2, "has"], [A3, 'ehm']])
asr_confnet.add([[B1, "Chinese"], [B2, "English"], [B3, 'cheap']])
asr_confnet.add([[C1, "restaurant"], [C2, "pub"], [C3, 'hotel']])
asr_confnet.merge()
asr_confnet.normalise()
asr_confnet.sort()
asr_nblist = asr_confnet.get_utterance_nblist()
sl.asr("user", "user1.wav", asr_nblist, asr_confnet)
slu_confnet = DialogueActConfusionNetwork()
slu_confnet.add(0.7, DialogueActItem('hello'))
slu_confnet.add(0.6, DialogueActItem('thankyou'))
slu_confnet.add(0.4, DialogueActItem('restart'))
slu_confnet.add(0.1, DialogueActItem('bye'))
slu_confnet.merge()
slu_confnet.normalise()
slu_confnet.sort()
slu_nblist = slu_confnet.get_da_nblist()
sl.slu("user", "user1.wav", slu_nblist, slu_confnet)
sl.turn("system")
sl.dialogue_act("system", "thankyou()")
sl.text("system", "Thank you.", cost = 1.0)
sl.rec_start("system", "system2.wav")
sl.rec_end("system2.wav")
sl.barge_in("system", tts_time = True)
sl.turn("user")
sl.rec_start("user", "user2.wav")
sl.rec_end("user2.wav")
sl.hangup("user")
def test_session_logger(self):
cfg = Config.load_configs(config=CONFIG_DICT, use_default=False)
sl = SessionLogger()
# test 3 calls at once
for i in range(3):
sess_dir = "./%d" % i
if not os.path.isdir(sess_dir):
os.mkdir(sess_dir)
sl.session_start(sess_dir)
sl.config('config = ' + unicode(cfg))
sl.header(cfg['Logging']["system_name"], cfg['Logging']["version"])
sl.input_source("voip")
sl.dialogue_rec_start(None, "both_complete_dialogue.wav")
sl.dialogue_rec_start("system", "system_complete_dialogue.wav")
sl.dialogue_rec_start("user", "user_complete_dialogue.wav")
sl.dialogue_rec_end("both_complete_dialogue.wav")
sl.dialogue_rec_end("system_complete_dialogue.wav")
sl.dialogue_rec_end("user_complete_dialogue.wav")
sl.turn("system")
sl.dialogue_act("system", "hello()")
sl.text("system", "Hello.")
sl.rec_start("system", "system1.wav")
sl.rec_end("system1.wav")
sl.turn("user")
sl.rec_start("user", "user1.wav")
sl.rec_end("user1.wav")
A1, A2, A3 = 0.90, 0.05, 0.05
B1, B2, B3 = 0.70, 0.20, 0.10
C1, C2, C3 = 0.80, 0.10, 0.10
asr_confnet = UtteranceConfusionNetwork()
asr_confnet.add([[A1, "want"], [A2, "has"], [A3, 'ehm']])
asr_confnet.add([[B1, "Chinese"], [B2, "English"], [B3, 'cheap']])
asr_confnet.add([[C1, "restaurant"], [C2, "pub"], [C3, 'hotel']])
asr_confnet.merge()
asr_confnet.normalise()
asr_confnet.sort()
asr_nblist = asr_confnet.get_utterance_nblist()
sl.asr("user", "user1.wav", asr_nblist, asr_confnet)
slu_confnet = DialogueActConfusionNetwork()
slu_confnet.add(0.7, DialogueActItem('hello'))
slu_confnet.add(0.6, DialogueActItem('thankyou'))
slu_confnet.add(0.4, DialogueActItem('restart'))
slu_confnet.add(0.1, DialogueActItem('bye'))
slu_confnet.merge()
slu_confnet.normalise()
slu_confnet.sort()
slu_nblist = slu_confnet.get_da_nblist()
sl.slu("user", "user1.wav", slu_nblist, slu_confnet)
sl.turn("system")
sl.dialogue_act("system", "thankyou()")
sl.text("system", "Thank you.", cost=1.0)
sl.rec_start("system", "system2.wav")
sl.rec_end("system2.wav")
sl.barge_in("system", tts_time=True)
sl.turn("user")
sl.rec_start("user", "user2.wav")
sl.rec_end("user2.wav")
sl.hangup("user")
def parse_1_best(self, obs, verbose=False):
"""Parse an utterance into a dialogue act."""
utterance = obs['utt']
if isinstance(utterance, UtteranceHyp):
# Parse just the utterance and ignore the confidence score.
utterance = utterance.utterance
# print 'Parsing utterance "{utt}".'.format(utt=utterance)
if verbose:
print 'Parsing utterance "{utt}".'.format(utt=utterance)
if self.preprocessing:
# the text normalisation
utterance = self.preprocessing.normalise_utterance(utterance)
abutterance, category_labels = self.abstract_utterance(utterance)
if verbose:
print 'After preprocessing: "{utt}".'.format(utt=abutterance)
print category_labels
else:
category_labels = dict()
# handle false positive alarms of abstraction
abutterance = abutterance.replace(('STOP=Metra', ), ('metra', ))
abutterance = abutterance.replace(('STOP=Nádraží', ), ('nádraží', ))
abutterance = abutterance.replace(('STOP=SME', ), ('sme', ))
abutterance = abutterance.replace((
'STOP=Bílá Hora',
'STOP=Železniční stanice',
), (
'STOP=Bílá Hora',
'železniční stanice',
))
abutterance = abutterance.replace(('TIME=now', 'bych', 'chtěl'),
('teď', 'bych', 'chtěl'))
abutterance = abutterance.replace(('STOP=Čím', 'se'), (
'čím',
'se',
))
abutterance = abutterance.replace((
'STOP=Lužin',
'STOP=Na Chmelnici',
), (
'STOP=Lužin',
'na',
'STOP=Chmelnici',
))
abutterance = abutterance.replace(('STOP=Konečná', 'zastávka'), (
'konečná',
'zastávka',
))
abutterance = abutterance.replace(('STOP=Konečná', 'STOP=Anděl'), (
'konečná',
'STOP=Anděl',
))
abutterance = abutterance.replace(
('STOP=Konečná stanice', 'STOP=Ládví'), (
'konečná',
'stanice',
'STOP=Ládví',
))
abutterance = abutterance.replace(('STOP=Výstupní', 'stanice', 'je'),
('výstupní', 'stanice', 'je'))
abutterance = abutterance.replace(('STOP=Nová', 'jiné'), (
'nové',
'jiné',
))
abutterance = abutterance.replace(('STOP=Nová', 'spojení'), (
'nové',
'spojení',
))
abutterance = abutterance.replace(('STOP=Nová', 'zadání'), (
'nové',
'zadání',
))
abutterance = abutterance.replace(
('STOP=Nová', 'TASK=find_connection'), (
'nový',
'TASK=find_connection',
))
abutterance = abutterance.replace((
'z',
'CITY=Liberk',
), (
'z',
'CITY=Liberec',
))
abutterance = abutterance.replace((
'do',
'CITY=Liberk',
), (
'do',
'CITY=Liberec',
))
abutterance = abutterance.replace((
'pauza',
'hrozně',
'STOP=Dlouhá',
), (
'pauza',
'hrozně',
'dlouhá',
))
abutterance = abutterance.replace((
'v',
'STOP=Praga',
), (
'v',
'CITY=Praha',
))
abutterance = abutterance.replace((
'na',
'STOP=Praga',
), (
'na',
'CITY=Praha',
))
abutterance = abutterance.replace(('po', 'STOP=Praga', 'ale'), (
'po',
'CITY=Praha',
))
abutterance = abutterance.replace((
'jsem',
'v',
'STOP=Metra',
), (
'jsem',
'v',
'VEHICLE=metro',
))
category_labels.add('CITY')
category_labels.add('VEHICLE')
# print 'After preprocessing: "{utt}".'.format(utt=abutterance)
# print category_labels
res_cn = DialogueActConfusionNetwork()
self.parse_non_speech_events(utterance, res_cn)
if len(res_cn) == 0:
# remove non speech events, they are not relevant for SLU
abutterance = abutterance.replace_all('_noise_', '').replace_all(
'_laugh_', '').replace_all('_ehm_hmm_',
'').replace_all('_inhale_', '')
if 'STOP' in category_labels:
self.parse_stop(abutterance, res_cn)
if 'CITY' in category_labels:
self.parse_city(abutterance, res_cn)
if 'TIME' in category_labels:
self.parse_time(abutterance, res_cn)
if 'DATE_REL' in category_labels:
self.parse_date_rel(abutterance, res_cn)
if 'AMPM' in category_labels:
self.parse_ampm(abutterance, res_cn)
if 'VEHICLE' in category_labels:
self.parse_vehicle(abutterance, res_cn)
if 'TASK' in category_labels:
self.parse_task(abutterance, res_cn)
self.parse_meta(utterance, res_cn)
res_cn.merge()
return res_cn
def parse_1_best(self, obs, verbose=False):
"""Parse an utterance into a dialogue act."""
utterance = obs['utt']
if isinstance(utterance, UtteranceHyp):
# Parse just the utterance and ignore the confidence score.
utterance = utterance.utterance
# print 'Parsing utterance "{utt}".'.format(utt=utterance)
if verbose:
print 'Parsing utterance "{utt}".'.format(utt=utterance)
if self.preprocessing:
# the text normalisation
utterance = self.preprocessing.normalise_utterance(utterance)
abutterance, category_labels = self.abstract_utterance(utterance)
if verbose:
print 'After preprocessing: "{utt}".'.format(utt=abutterance)
print category_labels
else:
category_labels = dict()
# handle false positive alarms of abstraction
abutterance = abutterance.replace(('STOP=Metra',), ('metra',))
abutterance = abutterance.replace(('STOP=Nádraží',), ('nádraží',))
abutterance = abutterance.replace(('STOP=SME',), ('sme',))
abutterance = abutterance.replace(('STOP=Bílá Hora', 'STOP=Železniční stanice',), ('STOP=Bílá Hora', 'železniční stanice',))
abutterance = abutterance.replace(('TIME=now','bych', 'chtěl'), ('teď', 'bych', 'chtěl'))
abutterance = abutterance.replace(('STOP=Čím','se'), ('čím', 'se',))
abutterance = abutterance.replace(('STOP=Lužin','STOP=Na Chmelnici',), ('STOP=Lužin','na','STOP=Chmelnici',))
abutterance = abutterance.replace(('STOP=Konečná','zastávka'), ('konečná', 'zastávka',))
abutterance = abutterance.replace(('STOP=Konečná','STOP=Anděl'), ('konečná', 'STOP=Anděl',))
abutterance = abutterance.replace(('STOP=Konečná stanice','STOP=Ládví'), ('konečná', 'stanice', 'STOP=Ládví',))
abutterance = abutterance.replace(('STOP=Výstupní', 'stanice', 'je'), ('výstupní', 'stanice', 'je'))
abutterance = abutterance.replace(('STOP=Nová','jiné'), ('nové', 'jiné',))
abutterance = abutterance.replace(('STOP=Nová','spojení'), ('nové', 'spojení',))
abutterance = abutterance.replace(('STOP=Nová','zadání'), ('nové', 'zadání',))
abutterance = abutterance.replace(('STOP=Nová','TASK=find_connection'), ('nový', 'TASK=find_connection',))
abutterance = abutterance.replace(('z','CITY=Liberk',), ('z', 'CITY=Liberec',))
abutterance = abutterance.replace(('do','CITY=Liberk',), ('do', 'CITY=Liberec',))
abutterance = abutterance.replace(('pauza','hrozně','STOP=Dlouhá',), ('pauza','hrozně','dlouhá',))
abutterance = abutterance.replace(('v','STOP=Praga',), ('v', 'CITY=Praha',))
abutterance = abutterance.replace(('na','STOP=Praga',), ('na', 'CITY=Praha',))
abutterance = abutterance.replace(('po','STOP=Praga', 'ale'), ('po', 'CITY=Praha',))
abutterance = abutterance.replace(('jsem','v','STOP=Metra',), ('jsem', 'v', 'VEHICLE=metro',))
category_labels.add('CITY')
category_labels.add('VEHICLE')
# print 'After preprocessing: "{utt}".'.format(utt=abutterance)
# print category_labels
res_cn = DialogueActConfusionNetwork()
self.parse_non_speech_events(utterance, res_cn)
if len(res_cn) == 0:
# remove non speech events, they are not relevant for SLU
abutterance = abutterance.replace_all('_noise_', '').replace_all('_laugh_', '').replace_all('_ehm_hmm_', '').replace_all('_inhale_', '')
if 'STOP' in category_labels:
self.parse_stop(abutterance, res_cn)
if 'CITY' in category_labels:
self.parse_city(abutterance, res_cn)
if 'TIME' in category_labels:
self.parse_time(abutterance, res_cn)
if 'DATE_REL' in category_labels:
self.parse_date_rel(abutterance, res_cn)
if 'AMPM' in category_labels:
self.parse_ampm(abutterance, res_cn)
if 'VEHICLE' in category_labels:
self.parse_vehicle(abutterance, res_cn)
if 'TASK' in category_labels:
self.parse_task(abutterance, res_cn)
self.parse_meta(utterance, res_cn)
res_cn.merge()
return res_cn
