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forced alignment by novoapi is performed.

master
yemaozi88 3 years ago
parent
commit
05e8a671c1
  1. BIN
      .vs/acoustic_model/v15/.suo
  2. 69
      acoustic_model/check_novoapi.py
  3. 21
      acoustic_model/novoapi_functions.py

BIN
.vs/acoustic_model/v15/.suo

69
acoustic_model/check_novoapi.py

@ -139,6 +139,71 @@ df_per_word = pd.DataFrame(index=[], columns=df_samples.keys())
for word in word_list:
df_samples_ = df_samples[df_samples['word']==word]
df_samples_ = df_samples_[df_samples_['frequency']>1]
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")
#df_per_word.to_excel(os.path.join(default.stimmen_dir, 'pronunciation_variants_novo70.xlsx'), encoding="utf-8")
## ===== forced alignment =====
if forced_alignment:
Results = pd.DataFrame(index=[],
columns=['filename', 'ipa', 'word', 'result_ipa', 'result_novo70', 'llh'])
for word in word_list:
#for word in ['Oor']:
# pronunciation variants top 3
df_per_word_ = df_per_word[df_per_word['word']==word]
df_per_word_ = df_per_word_.sort_values('frequency', ascending=False)
if len(df_per_word_) < 3: # pauw, rozen
pronunciation_ipa = list(df_per_word_['ipa'])
elif word=='Reuzenrad':
pronunciation_ipa = [
df_per_word_.iloc[0]['ipa'],
df_per_word_.iloc[1]['ipa'],
df_per_word_.iloc[2]['ipa'],
df_per_word_.iloc[3]['ipa']]
else:
# oog, oor, reus, roeiboot
pronunciation_ipa = [
df_per_word_.iloc[0]['ipa'],
df_per_word_.iloc[1]['ipa'],
df_per_word_.iloc[2]['ipa']]
#print("{0}: {1}".format(word, pronunciation_ipa))
# samples for the word
df_ = df[df['word']==word]
# samples in which all pronunciations are written in novo70.
samples = df_.query("ipa in @pronunciation_ipa")
results = pd.DataFrame(index=[],
columns=['filename', 'ipa', 'word', 'result_ipa', 'result_novo70', 'llh'])
#j = 0
for i in range(0, len(samples)):
sample = samples.iloc[i]
wav_file = os.path.join(default.stimmen_wav_dir, sample['filename'])
if os.path.exists(wav_file):
#j += 1
#print('{0} - {1}'.format(word, i))
pronunciation_ipa_ = [ipa.replace(':', 'ː') for ipa in pronunciation_ipa]
result = novoapi_functions.forced_alignment(wav_file, word, pronunciation_ipa_)
result_ipa, result_novo70, llh = novoapi_functions.result2pronunciation(result, word)
result_ = pd.Series([
sample['filename'],
sample['ipa'],
sample['word'],
' '.join(result_ipa),
' '.join(result_novo70),
llh
], index=results.columns)
results = results.append(result_, ignore_index = True)
print('{0}/{1}: answer {2} - prediction {3}'.format(
i+1, len(samples), result_['ipa'], result_['result_ipa']))
if len(results) > 0:
Results = Results.append(results, ignore_index = True)
Results.to_excel(os.path.join(default.stimmen_dir, 'Results.xlsx'), encoding="utf-8")
else:
Results_xlsx = pd.ExcelFile(os.path.join(default.stimmen_dir, 'Results.xlsx'), encoding="utf-8")
R = pd.read_excel(Results_xlsx, 'Sheet1')

21
acoustic_model/novoapi_functions.py

@ -36,10 +36,29 @@ def load_phonset():
phoneset_novo70.append(novo70)
translation_key_ipa2novo70[ipa] = novo70
translation_key_novo702ipa[novo70] = ipa
# As per Nederlandse phoneset_aki.xlsx recieved from David
# [ɔː] oh / ohr # from ipa->novo70, only oh is used.
# [ɪː] ih / ihr # from ipa->novo70, only ih is used.
# [iː] iy
# [œː] uh
# [ɛː] eh
# [w] wv in IPA written as ʋ.
extra_ipa = ['ɔː', 'ɪː', '', 'œː', 'ɛː', 'ʋ']
extra_novo70 = ['oh', 'ih', 'iy', 'uh', 'eh', 'wv']
for ipa, novo70 in zip(extra_ipa, extra_novo70):
phoneset_ipa.append(ipa)
phoneset_novo70.append(novo70)
translation_key_ipa2novo70[ipa] = novo70
translation_key_novo702ipa[novo70] = ipa
translation_key_novo702ipa['ohr'] = 'ɔː'
translation_key_novo702ipa['ihr'] = 'ɪː'
phoneset_ipa = np.unique(phoneset_ipa)
phoneset_novo70 = np.unique(phoneset_novo70)
return
return phoneset_ipa, phoneset_novo70, translation_key_ipa2novo70, translation_key_novo702ipa
def multi_character_tokenize(line, multi_character_tokens):

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