dataset for experiments in check_novoapi is updated.

acoustic_model/acoustic_model.pyproj

@@ -4,7 +4,7 @@
     <SchemaVersion>2.0</SchemaVersion>
     <ProjectGuid>4d8c8573-32f0-4a62-9e62-3ce5cc680390</ProjectGuid>
     <ProjectHome>.</ProjectHome>
-    <StartupFile>fame_hmm.py</StartupFile>
+    <StartupFile>check_novoapi.py</StartupFile>
     <SearchPath>
     </SearchPath>
     <WorkingDirectory>.</WorkingDirectory>

acoustic_model/check_novoapi.py

@@ -29,48 +29,47 @@ forced_alignment_novo70 = True
 
 
 ## ===== load novo phoneset =====
-phoneset_ipa, phoneset_novo70, translation_key_ipa2novo70, translation_key_novo702ipa = novoapi_functions.load_phonset()
+phoneset_ipa, phoneset_novo70, translation_key_ipa2novo70, translation_key_novo702ipa = novoapi_functions.load_novo70_phoneset()
 
 
 ## ===== extract pronunciations written in novo70 only (not_in_novo70) =====
 
-# As per Nederlandse phoneset_aki.xlsx recieved from David
+
-# [ɔː] oh / ohr
-# [ɪː] ih / ihr
-# [iː] iy
-# [œː] uh
-# [ɛː] eh
-# [w] wv in IPA written as ʋ. 
-david_suggestion = ['ɔː', 'ɪː', 'iː', 'œː', 'ɛː', 'w']
 
 ## read pronunciation variants.
-stimmen_transcription_ = pd.ExcelFile(default.stimmen_transcription_xlsx)
+#stimmen_transcription_ = pd.ExcelFile(default.stimmen_transcription_xlsx)
-df = pd.read_excel(stimmen_transcription_, 'frequency')
+#df = pd.read_excel(stimmen_transcription_, 'frequency')
-transcription_ipa = list(df['IPA'])
+#transcription_ipa = list(df['IPA'])
 
-# transcription mistake?
-transcription_ipa = [ipa.replace(';', 'ː') for ipa in transcription_ipa if not ipa=='pypɪl' and not pd.isnull(ipa)]
-transcription_ipa = [ipa.replace('ˑ', '') for ipa in transcription_ipa] # only one case.
 
-not_in_novo70 = []
+stimmen_test_dir = r'c:\OneDrive\Research\rug\_data\stimmen_test'
-all_in_novo70 = []
+df = stimmen_functions.load_transcriptions_novo70(stimmen_test_dir)
-for ipa in transcription_ipa:
-	ipa = ipa.replace(':', 'ː')
-	ipa = convert_phone_set.split_ipa(ipa)
 
-	# list of phones not in novo70 phoneset.
-	not_in_novo70_ = [phone for phone in ipa 
-				   if not phone in phoneset_ipa and not phone in david_suggestion]
-	not_in_novo70_ = [phone.replace('sp', '') for phone in not_in_novo70_]
-	not_in_novo70_ = [phone.replace(':', '') for phone in not_in_novo70_]
-	not_in_novo70_ = [phone.replace('ː', '') for phone in not_in_novo70_]
 	
-	if len(not_in_novo70_) == 0:
-		all_in_novo70.append(''.join(ipa))
 
-	#translation_key.get(phone, phone)
+## transcription mistake?
-	not_in_novo70.extend(not_in_novo70_)
+#transcription_ipa = [ipa.replace(';', 'ː') for ipa in transcription_ipa if not ipa=='pypɪl' and not pd.isnull(ipa)]
-not_in_novo70_list = list(set(not_in_novo70))
+#transcription_ipa = [ipa.replace('ˑ', '') for ipa in transcription_ipa] # only one case.
+
+#not_in_novo70 = []
+#all_in_novo70 = []
+#for ipa in transcription_ipa:
+#	ipa = ipa.replace(':', 'ː')
+#	ipa = convert_phone_set.split_ipa(ipa)
+
+#	# list of phones not in novo70 phoneset.
+#	not_in_novo70_ = [phone for phone in ipa 
+#				   if not phone in phoneset_ipa and not phone in david_suggestion]
+#	not_in_novo70_ = [phone.replace('sp', '') for phone in not_in_novo70_]
+#	not_in_novo70_ = [phone.replace(':', '') for phone in not_in_novo70_]
+#	not_in_novo70_ = [phone.replace('ː', '') for phone in not_in_novo70_]
+
+#	if len(not_in_novo70_) == 0:
+#		all_in_novo70.append(''.join(ipa))
+
+#	#translation_key.get(phone, phone)
+#	not_in_novo70.extend(not_in_novo70_)
+#not_in_novo70_list = list(set(not_in_novo70))
 
 
 ## check which phones used in stimmen but not in novo70
@@ -85,41 +84,43 @@ not_in_novo70_list = list(set(not_in_novo70))
 # [ʊ] 'ʊ'(1) --> can be ʏ (uh)??
 # [χ] --> can be x??
 
-def search_phone_ipa(x, phone_list):
+#def search_phone_ipa(x, phone_list):
-	x_in_item = []
+#	x_in_item = []
-	for ipa in phone_list:
+#	for ipa in phone_list:
-		ipa_original = ipa
+#		ipa_original = ipa
-		ipa = ipa.replace(':', 'ː')
+#		ipa = ipa.replace(':', 'ː')
-		ipa = convert_phone_set.split_ipa(ipa)
+#		ipa = convert_phone_set.split_ipa(ipa)
-		if x in ipa and not x+':' in ipa:
+#		if x in ipa and not x+':' in ipa:
-			x_in_item.append(ipa_original)
+#			x_in_item.append(ipa_original)
-	return x_in_item
+#	return x_in_item
 #search_phone_ipa('ø', transcription_ipa)
 
 
 ## ===== load all transcriptions (df) =====
-df = stimmen_functions.load_transcriptions()
+#df = stimmen_functions.load_transcriptions()
 word_list = [i for i in list(set(df['word'])) if not pd.isnull(i)]
 word_list = sorted(word_list)
 
 
 ## check frequency of each pronunciation variants
-cols = ['word', 'ipa', 'frequency']
+#cols = ['word', 'ipa', 'frequency']
-df_samples = pd.DataFrame(index=[], columns=cols)
+#df_samples = pd.DataFrame(index=[], columns=cols)
-for ipa in all_in_novo70:
+#for ipa in all_in_novo70:
-	ipa = ipa.replace('ː', ':')
+#	ipa = ipa.replace('ː', ':')
-	samples = df[df['ipa'] == ipa]
+#	samples = df[df['ipa'] == ipa]
-	word = list(set(samples['word']))[0]
+#	word = list(set(samples['word']))[0]
-	samples_Series = pd.Series([word, ipa, len(samples)], index=df_samples.columns)
+#	samples_Series = pd.Series([word, ipa, len(samples)], index=df_samples.columns)
-	df_samples = df_samples.append(samples_Series, ignore_index=True)
+#	df_samples = df_samples.append(samples_Series, ignore_index=True)
 
 # each word
-df_per_word = pd.DataFrame(index=[], columns=df_samples.keys())
+#df_per_word = pd.DataFrame(index=[], columns=df_samples.keys())
 
-for word in word_list:
+#for word in word_list:
-	df_samples_ = df_samples[df_samples['word']==word]
+word = word_list[2]
-	df_samples_ = df_samples_[df_samples_['frequency']>2]
+df_ = df[df['word']==word]
-	df_per_word = df_per_word.append(df_samples_, ignore_index=True)
+np.unique(list(df_['ipa']))
+	#df_samples_ = df_samples_[df_samples_['frequency']>2]
+	#df_per_word = df_per_word.append(df_samples_, ignore_index=True)
 #df_per_word.to_excel(os.path.join(default.stimmen_dir, 'pronunciation_variants_novo70.xlsx'), encoding="utf-8")
 
 

acoustic_model/fame_functions.py

@@ -352,9 +352,6 @@ def fix_lexicon(lexicon_file):
 	return
 
 
-#def add_sp_to_lexicon(lexicon_file):
-
-
 def word2htk(word):
 	return ''.join([fame_asr.translation_key_word2htk.get(i, i) for i in word])
 

acoustic_model/novoapi_functions.py

@@ -174,6 +174,8 @@ def forced_alignment(wav_file, word, pronunciation_ipa):
 	p.add_argument("--user", default='martijn.wieling')
 	p.add_argument("--password", default='xxxxxx')
 
+
+
 	args = p.parse_args()
 	
 	rec = session.Recognizer(grammar_version="1.0", lang="nl", snodeid=101, user=args.user, password=args.password, keepopen=True) # , modeldir=modeldir)
@@ -194,6 +196,24 @@ def result2pronunciation(result, word):
 	return pronunciation_ipa, pronunciation_novo70, llh
 
 
+def phones_not_in_novo70(ipa):
+	""" extract phones which is not in novo70 phoneset. """
+
+	phoneset_ipa, _, _, _ = load_novo70_phoneset()
+
+	# As per Nederlandse phoneset_aki.xlsx recieved from David
+	# [ɔː] oh / ohr
+	# [ɪː] ih / ihr
+	# [iː] iy
+	# [œː] uh
+	# [ɛː] eh
+	# [w] wv in IPA written as ʋ. 
+	david_suggestion = ['ɔː', 'ɪː', 'iː', 'œː', 'ɛː', 'w']
+
+	return [phone for phone in split_ipa(ipa) 
+				   if not phone in phoneset_ipa and not phone in david_suggestion]
+
+
 if __name__ == 'main':
 	pronunciation_ipa = ['rø:s', 'mɑn', 'mɑntsjə']
 	#grammar = make_grammar('reus', pronunciation_ipa)

acoustic_model/stimmen_functions.py

@@ -7,6 +7,7 @@ import pandas as pd
 import convert_xsampa2ipa
 import defaultfiles as default
 import fame_functions
+import novoapi_functions
 
 
 def _load_transcriptions():
@@ -67,6 +68,19 @@ def load_transcriptions_clean(clean_wav_dir):
 	return df_clean
 
 
+def load_transcriptions_novo70(clean_wav_dir):
+	""" extract rows of which ipa is written in novo70 phonset. """
+	df = load_transcriptions_clean(clean_wav_dir)
+
+	df_novo70 = pd.DataFrame(index=[], columns=list(df.keys()))
+	for index, row in df.iterrows():
+		not_in_novo70 = novoapi_functions.phones_not_in_novo70(row['ipa'])
+		if len(not_in_novo70) == 0:
+			df_novo70 = df_novo70.append(row, ignore_index=True)
+
+	return df_novo70
+
+
 def add_row_htk(df):
 	""" df['htk'] is made from df['ipa'] and added. """
 	htk = []