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phonset is given as fame_phoneset.py. translation key is obtained based on the information.

master
yemaozi88 3 years ago
parent
commit
813f013d7a
  1. BIN
      .vs/acoustic_model/v15/.suo
  2. BIN
      _tmp/phone_to_be_searched.npy
  3. BIN
      _tmp/translation_key.npy
  4. 7
      acoustic_model.sln
  5. BIN
      acoustic_model/__pycache__/defaultfiles.cpython-36.pyc
  6. 6
      acoustic_model/acoustic_model.pyproj
  7. 29
      acoustic_model/convert_phone_set.py
  8. 19
      acoustic_model/defaultfiles.py
  9. 98
      acoustic_model/fame_functions.py
  10. 12
      acoustic_model/fame_hmm.py
  11. 55
      acoustic_model/fame_phoneset.py

BIN
.vs/acoustic_model/v15/.suo

BIN
_tmp/phone_to_be_searched.npy

BIN
_tmp/translation_key.npy

7
acoustic_model.sln

@ -10,7 +10,6 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Solution Items", "Solution
..\forced_alignment\forced_alignment\__init__.py = ..\forced_alignment\forced_alignment\__init__.py
..\forced_alignment\forced_alignment\convert_phone_set.py = ..\forced_alignment\forced_alignment\convert_phone_set.py
..\toolbox\evaluation.py = ..\toolbox\evaluation.py
..\toolbox\toolbox\file_handling.py = ..\toolbox\toolbox\file_handling.py
..\forced_alignment\forced_alignment\htk_dict.py = ..\forced_alignment\forced_alignment\htk_dict.py
..\forced_alignment\forced_alignment\lexicon.py = ..\forced_alignment\forced_alignment\lexicon.py
..\forced_alignment\forced_alignment\mlf.py = ..\forced_alignment\forced_alignment\mlf.py
@ -23,7 +22,7 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Solution Items", "Solution
..\forced_alignment\forced_alignment\test_environment.py = ..\forced_alignment\forced_alignment\test_environment.py
EndProjectSection
EndProject
Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "pyhtk", "..\pyhtk\pyhtk\pyhtk.pyproj", "{75FCEFAF-9397-43FC-8189-DE97ADB77AA5}"
Project("{888888A0-9F3D-457C-B088-3A5042F75D52}") = "toolbox", "..\toolbox\toolbox.pyproj", "{F0D46C9C-51C6-4989-8A2F-35F2A0C048BE}"
EndProject
Global
GlobalSection(SolutionConfigurationPlatforms) = preSolution
@ -33,8 +32,8 @@ Global
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{4D8C8573-32F0-4A62-9E62-3CE5CC680390}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
{4D8C8573-32F0-4A62-9E62-3CE5CC680390}.Release|Any CPU.ActiveCfg = Release|Any CPU
{75FCEFAF-9397-43FC-8189-DE97ADB77AA5}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
{75FCEFAF-9397-43FC-8189-DE97ADB77AA5}.Release|Any CPU.ActiveCfg = Release|Any CPU
{F0D46C9C-51C6-4989-8A2F-35F2A0C048BE}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
{F0D46C9C-51C6-4989-8A2F-35F2A0C048BE}.Release|Any CPU.ActiveCfg = Release|Any CPU
EndGlobalSection
GlobalSection(SolutionProperties) = preSolution
HideSolutionNode = FALSE

BIN
acoustic_model/__pycache__/defaultfiles.cpython-36.pyc

6
acoustic_model/acoustic_model.pyproj

@ -23,12 +23,18 @@
</PropertyGroup>
<ItemGroup>
<Compile Include="check_novoapi.py" />
<Compile Include="convert_phone_set.py">
<SubType>Code</SubType>
</Compile>
<Compile Include="convert_xsampa2ipa.py">
<SubType>Code</SubType>
</Compile>
<Compile Include="defaultfiles.py">
<SubType>Code</SubType>
</Compile>
<Compile Include="fame_phoneset.py">
<SubType>Code</SubType>
</Compile>
<Compile Include="fa_test.py">
<SubType>Code</SubType>
</Compile>

29
acoustic_model/convert_phone_set.py

@ -0,0 +1,29 @@
"""Module to convert phonemes."""
def multi_character_tokenize(line, multi_character_tokens):
"""Tries to match one of the tokens in multi_character_tokens at each position of line, starting at position 0,
if so tokenizes and eats that token. Otherwise tokenizes a single character"""
while line != '':
for token in multi_character_tokens:
if line.startswith(token) and len(token) > 0:
yield token
line = line[len(token):]
break
else:
yield line[:1]
line = line[1:]
def split_word(word, multi_character_phones):
"""
Split a line by given phoneset.
Args:
word (str): one word written in given phoneset.
multi_character_phones:
Returns:
word_seperated (str): the word splitted in given phoneset.
"""
return [phone for phone in multi_character_tokenize(word.strip(), multi_character_phones)]

19
acoustic_model/defaultfiles.py

@ -4,7 +4,8 @@ import os
#cygwin_dir = r'C:\cygwin64\home\Aki\acoustic_model'
htk_dir = r'C:\Aki\htk_fame'
#htk_dir = r'C:\Aki\htk_fame'
htk_dir = r'c:\OneDrive\Research\rug\experiments\acoustic_model\fame\htk'
config_hcopy = os.path.join(htk_dir, 'config', 'config.HCopy')
#config_train = os.path.join(cygwin_dir, 'config', 'config.train')
@ -28,22 +29,22 @@ config_hcopy = os.path.join(htk_dir, 'config', 'config.HCopy')
#filePhoneList = config['pyHTK']['filePhoneList']
#AcousticModel = config['pyHTK']['AcousticModel']
repo_dir = r'C:\Users\A.Kunikoshi\source\repos'
repo_dir = r'C:\Users\Aki\source\repos'
ipa_xsampa_converter_dir = os.path.join(repo_dir, 'ipa-xsama-converter')
forced_alignment_module_dir = os.path.join(repo_dir, 'forced_alignment')
accent_classification_dir = os.path.join(repo_dir, 'accent_classification', 'accent_classification')
pyhtk_dir = os.path.join(repo_dir, 'pyhtk', 'pyhtk')
toolbox_dir = os.path.join(repo_dir, 'toolbox', 'toolbox')
#pyhtk_dir = os.path.join(repo_dir, 'pyhtk', 'pyhtk')
toolbox_dir = os.path.join(repo_dir, 'toolbox')
htk_config_dir = r'c:\Users\A.Kunikoshi\source\repos\forced_alignment\forced_alignment\data\htk\preset_models\aki_dutch_2017'
config_hvite = os.path.join(htk_config_dir, 'config.HVite')
#htk_config_dir = r'c:\Users\A.Kunikoshi\source\repos\forced_alignment\forced_alignment\data\htk\preset_models\aki_dutch_2017'
#config_hvite = os.path.join(htk_config_dir, 'config.HVite')
#acoustic_model = os.path.join(htk_config_dir, 'hmmdefs.compo')
acoustic_model = r'c:\cygwin64\home\A.Kunikoshi\acoustic_model\model\barbara\hmm128-2\hmmdefs.compo'
phonelist_txt = os.path.join(htk_config_dir, 'phonelist.txt')
#acoustic_model = r'c:\cygwin64\home\A.Kunikoshi\acoustic_model\model\barbara\hmm128-2\hmmdefs.compo'
#phonelist_txt = os.path.join(htk_config_dir, 'phonelist.txt')
WSL_dir = r'C:\OneDrive\WSL'
#fame_dir = os.path.join(WSL_dir, 'kaldi-trunk', 'egs', 'fame')
fame_dir = r'f:\_corpus\fame'
fame_dir = r'd:\_corpus\fame'
fame_s5_dir = os.path.join(fame_dir, 's5')
fame_corpus_dir = os.path.join(fame_dir, 'corpus')

98
acoustic_model/fame_functions.py

@ -1,5 +1,5 @@
import os
os.chdir(r'C:\Users\A.Kunikoshi\source\repos\acoustic_model\acoustic_model')
os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
import sys
from collections import Counter
@ -9,6 +9,8 @@ import numpy as np
import pandas as pd
import defaultfiles as default
import fame_phoneset
import convert_phone_set
#sys.path.append(default.forced_alignment_module_dir)
#from forced_alignment import convert_phone_set
@ -213,40 +215,74 @@ def get_phonelist(lexicon_asr):
lex = load_lexicon(lexicon_asr)
return set(' '.join(lex['pronunciation']).split(' '))
import time
timer_start = time.time()
def extract_unknown_phones(word_list, known_phones):
return [i for i in word_list if not i in known_phones]
#def get_translation_key():
dir_tmp = r'c:\Users\A.Kunikoshi\source\repos\acoustic_model\_tmp'
lexicon_ipa = r'f:\_corpus\FAME\lexicon\lex.ipa'
lexicon_asr = r'f:\_corpus\FAME\lexicon\lex.asr'
lex_ipa = load_lexicon(lexicon_ipa)
lex_asr = load_lexicon(lexicon_asr)
if 0:
phone_to_be_searched = get_phonelist(lexicon_asr)
translation_key = dict()
for word in lex_asr['word']:
if np.sum(lex_asr['word'] == word) == 1 and np.sum(lex_ipa['word'] == word) == 1:
asr = lex_asr[lex_asr['word'] == word].iat[0, 1]
ipa = lex_ipa[lex_ipa['word'] == word].iat[0, 1]
if __name__ == '__main__':
import time
timer_start = time.time()
#def get_translation_key():
dir_tmp = r'c:\Users\Aki\source\repos\acoustic_model\_tmp'
lexicon_ipa = r'd:\_corpus\FAME\lexicon\lex.ipa'
lexicon_asr = r'd:\_corpus\FAME\lexicon\lex.asr'
lex_ipa = load_lexicon(lexicon_ipa)
lex_asr = load_lexicon(lexicon_asr)
if 1:
phone_to_be_searched = fame_phoneset.phoneset_ipa[:]
translation_key = dict()
for word in lex_ipa['word']:
if np.sum(lex_ipa['word'] == word) == 1 and np.sum(lex_asr['word'] == word) == 1:
ipa = lex_ipa[lex_ipa['word'] == word].iat[0, 1]
asr = lex_asr[lex_asr['word'] == word].iat[0, 1]
asr_list = asr.split(' ')
# if there are phones which is not in phone_to_be_searched
if len([True for i in asr_list if i in phone_to_be_searched]) > 0:
if(len(ipa) == len(asr_list)):
print("{0}: {1} --> {2}".format(word, ipa, asr))
for ipa_, asr_ in zip(ipa, asr_list):
if asr_ in phone_to_be_searched:
#if not translation_key[ipa_] == asr_:
ipa_list = convert_phone_set.split_word(ipa, fame_phoneset.multi_character_phones_ipa)
asr_list = asr.split(' ')
# if there are phones which is not in phone_to_be_searched
#if len([True for i in asr_list if i in phone_to_be_searched]) > 0:
if(len(ipa_list) == len(asr_list)):
print("{0}: {1} --> {2}".format(word, ipa_list, asr_list))
for ipa_, asr_ in zip(ipa_list, asr_list):
if ipa_ in phone_to_be_searched:
translation_key[ipa_] = asr_
phone_to_be_searched.remove(asr_)
phone_to_be_searched.remove(ipa_)
print("elapsed time: {}".format(time.time() - timer_start))
print("elapsed time: {}".format(time.time() - timer_start))
np.save(os.path.join(dir_tmp, 'translation_key.npy'), translation_key)
np.save(os.path.join(dir_tmp, 'phone_to_be_searched.npy'), phone_to_be_searched)
else:
translation_key = np.load(os.path.join(dir_tmp, 'translation_key.npy')).item()
phone_to_be_searched = np.load(os.path.join(dir_tmp, 'phone_to_be_searched.npy')).item()
np.save(os.path.join(dir_tmp, 'translation_key.npy'), translation_key)
np.save(os.path.join(dir_tmp, 'phone_to_be_searched.npy'), phone_to_be_searched)
else:
translation_key = np.load(os.path.join(dir_tmp, 'translation_key.npy')).item()
phone_to_be_searched = np.load(os.path.join(dir_tmp, 'phone_to_be_searched.npy')).item()
#phone_unknown = list(phone_to_be_searched)
##phone_unknown.remove('')
#phone_known = list(translation_key.keys())
#p = phone_unknown[0]
### extract lines which contains 'unknown' phone.
#lex_ipa_ = lex_ipa[lex_ipa['pronunciation'].str.count(p)>0]
##phone_unknown_ = phone_unknown[:]
##phone_unknown_.remove(p)
#phone_known_ = phone_known[:]
#phone_known_.append(p)
#for index, row in lex_ipa_.iterrows():
# ipa = row['pronunciation']
# phone_extract_unknown_phones(asr_list, phone_known_):
# # check the number of phones in phone_unknown_
# if len([True for i in asr_list if i in phone_unknown_]) == 0:
# word = row['word']
# ipa = lex_ipa[lex_ipa['word'] == word].iat[0, 1]
# print("{0}: {1} --> {2}".format(word, ipa, asr))
# #print("{0}:{1}".format(index, row['pronunciation']))

12
acoustic_model/fame_hmm.py

@ -1,6 +1,6 @@
import sys
import os
os.chdir(r'C:\Users\A.Kunikoshi\source\repos\acoustic_model\acoustic_model')
os.chdir(r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model')
import tempfile
#import configparser
@ -12,10 +12,9 @@ import tempfile
import fame_functions
import defaultfiles as default
sys.path.append(default.pyhtk_dir)
import pyhtk
sys.path.append(default.toolbox_dir)
import file_handling
import file_handling as fh
from htk import pyhtk
## ======================= user define =======================
@ -94,7 +93,7 @@ if extract_features:
hcopy_scp.close()
#hcopy_scp = os.path.join(default.htk_dir, 'tmp', 'HCopy.scp')
# get a list of features (hcopy.scp) from the filelist in FAME! corpus
## get a list of features (hcopy.scp) from the filelist in FAME! corpus
feature_dir_ = os.path.join(feature_dir, dataset)
if not os.path.exists(feature_dir_):
os.makedirs(feature_dir_)
@ -110,6 +109,7 @@ if extract_features:
# a script file for HCompV
print(">>> making a script file for HCompV... \n")
## ======================= make a list of features =======================
#if make_feature_list:
# print("==== make a list of features ====\n")
@ -121,7 +121,7 @@ if extract_features:
hcompv_scp = os.path.join(tmp_dir, dataset + '.scp')
#am_func.make_filelist(feature_dir, hcompv_scp)
file_handling.make_filelist(feature_dir_, hcompv_scp, '.mfc')
fh.make_filelist(feature_dir_, hcompv_scp, '.mfc')
## ======================= convert lexicon from ipa to fame_htk =======================

55
acoustic_model/fame_phoneset.py

@ -0,0 +1,55 @@
phoneset_ipa = [
# vowels
'',
'y',
'i',
'i:',
'ɪ',
'ɪ:',
'e',
'e:',
'ə',
'ə:',
'ɛ',
'ɛ:',
'a',
'a:',
'',
'ú',
'u',
'u:',
'ü',
'ü:',
'o',
'o:',
'ö',
'ö:',
'ɔ',
'ɔ:',
'ɔ̈',
'ɔ̈:',
# plosives
'p',
'b',
't',
'd',
'k',
'g',
# nasals
'm',
'n',
'ŋ',
# fricatives
'f',
'v',
's',
's:',
'z',
'x',
'h',
]
multi_character_phones_ipa = [i for i in phoneset_ipa if len(i) > 1]
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