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xsampa to ipa conversion is added.

master
yemaozi88 3 years ago
parent
commit
5fb05ddab2
  1. BIN
      .vs/acoustic_model/v15/.suo
  2. 2
      acoustic_model/acoustic_model.py
  3. 2
      acoustic_model/config.ini
  4. 79
      acoustic_model/performance_check.py

BIN
.vs/acoustic_model/v15/.suo

2
acoustic_model/acoustic_model.py

@ -13,7 +13,7 @@ import pandas as pd
repo_dir = 'C:\\Users\\Aki\\source\\repos\\acoustic_model'
curr_dir = repo_dir + '\\acoustic_model'
config_ini = curr_dir + '\\config.ini'
output_dir = 'd:\\OneDrive\\Research\\rug\\experiments\\friesian\\acoustic_model'
output_dir = 'C:\\OneDrive\\Research\\rug\\experiments\\friesian\\acoustic_model'
forced_alignment_module = 'C:\\Users\\Aki\\source\\repos\\forced_alignment'
dataset_list = ['devel', 'test', 'train']

2
acoustic_model/config.ini

@ -2,4 +2,4 @@
config_hcopy = c:\cygwin64\home\Aki\acoustic_model\config\config.HCopy
config_train = c:\cygwin64\home\Aki\acoustic_model\config\config.train
mkhmmdefs_pl = c:\cygwin64\home\Aki\acoustic_model\src\acoustic_model\mkhmmdefs.pl
FAME_dir = d:\OneDrive\Research\rug\experiments\friesian\corpus
FAME_dir = c:\OneDrive\Research\rug\experiments\friesian\corpus

79
acoustic_model/performance_check.py

@ -2,25 +2,54 @@ import os
import sys
import csv
import subprocess
import configparser
import numpy as np
import convert_xsampa2ipa
import pandas as pd
## ======================= user define =======================
curr_dir = r'C:\Users\Aki\source\repos\acoustic_model\acoustic_model'
config_ini = curr_dir + '\\config.ini'
forced_alignment_module = r'C:\Users\Aki\source\repos\forced_alignment'
ipa_xsampa_converter_dir = r'C:\Users\Aki\source\repos\ipa-xsama-converter'
csvfile = r"C:\OneDrive\Research\rug\stimmen\Frisian Variants Picture Task Stimmen.csv"
# procedure
## ======================= add paths =======================
sys.path.append(forced_alignment_module)
from forced_alignment import convert_phone_set
# for interactive window
sys.path.append(curr_dir)
import convert_xsampa2ipa
import acoustic_model_functions as am_func
## ======================= load variables =======================
config = configparser.ConfigParser()
config.sections()
config.read(config_ini)
FAME_dir = config['Settings']['FAME_dir']
lex_asr = FAME_dir + '\\lexicon\\lex.asr'
lex_asr_htk = FAME_dir + '\\lexicon\\lex.asr_htk'
## ======================= check phones included in FAME! =======================
# the phones used in the lexicon.
#phonelist = am_func.get_phonelist(lex_htk)
# the lines which include a specific phone.
#lines = am_func.find_phone(lex_asr, 'x')
## ======================= convert phones ======================
mapping = convert_xsampa2ipa.load_converter('xsampa', 'ipa', ipa_xsampa_converter_dir)
#word_xsampa = 'e:j@X'
#word_ipa = convert_xsampa2ipa.conversion('xsampa', 'ipa', mapping, word_xsampa)
with open(csvfile, encoding="utf-8") as fin:
lines = csv.reader(fin, delimiter=';', lineterminator="\n", skipinitialspace=True)
@ -33,14 +62,42 @@ with open(csvfile, encoding="utf-8") as fin:
if line[1] is not '' and len(line) > 5:
filenames.append(line[0])
words.append(line[1])
word_xsampa = line[3]
word_ipa = convert_xsampa2ipa.conversion('xsampa', 'ipa', mapping, word_xsampa)
word_ipa = word_ipa.replace('ː', ':')
word_famehtk = convert_phone_set.ipa2famehtk(word_ipa)
pronunciations.append(word_famehtk)
phonelist = ' '.join(pronunciations)
np.unique(phonelist.split(' '))
pron_xsampa = line[3]
pron_ipa = convert_xsampa2ipa.conversion('xsampa', 'ipa', mapping, pron_xsampa)
pron_ipa = pron_ipa.replace('ː', ':')
pron_famehtk = convert_phone_set.ipa2famehtk(pron_ipa)
# adjust to phones used in the acoustic model.
pron_famehtk = pron_famehtk.replace('sp', 'sil')
pron_famehtk = pron_famehtk.replace('ce :', 'ce') # because ceh is ignored.
pron_famehtk = pron_famehtk.replace('w :', 'wh')
pron_famehtk = pron_famehtk.replace('e :', 'eh')
pron_famehtk = pron_famehtk.replace('eh :', 'eh')
pron_famehtk = pron_famehtk.replace('ih :', 'ih')
#translation_key = {'sp': 'sil', 'ce :': 'ceh', 'w :': 'wh'}
#pron = []
#for phoneme in pron_famehtk.split(' '):
# pron.append(translation_key.get(phoneme, phoneme))
#pronunciations.append(' '.join(pron_famehtk))
pronunciations.append(pron_famehtk)
filenames = np.array(filenames)
words = np.array(words)
pronunciations = np.array(pronunciations)
del line, lines
del pron_xsampa, pron_ipa, pron_famehtk
# check if all phones are in the phonelist of the acoustic model.
#phonelist = ' '.join(pronunciations)
#np.unique(phonelist.split(' '))
#phonelist.find(':')
# make dict files.
word_list = np.unique(words)
word_id = 1
word = word_list[word_id]
## ======================= forced alignment =======================

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