67 lines
1.9 KiB
Python
67 lines
1.9 KiB
Python
import os
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import sys
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import tempfile
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import configparser
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import subprocess
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## ======================= user define =======================
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repo_dir = 'C:\\Users\\Aki\\source\\repos\\acoustic_model'
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curr_dir = repo_dir + '\\acoustic_model'
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config_ini = curr_dir + '\\config.ini'
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output_dir = 'd:\\OneDrive\\Research\\rug\\experiments\\friesian\\acoustic_model'
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sys.path.append(os.path.join(os.path.dirname(sys.path[0]), curr_dir))
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import acoustic_model_functions as am_func
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## ======================= load variables =======================
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config = configparser.ConfigParser()
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config.sections()
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config.read(config_ini)
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config_hcopy = config['Settings']['config_hcopy']
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config_train = config['Settings']['config_train']
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FAME_dir = config['Settings']['FAME_dir']
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dataset_list = ['devel', 'test', 'train']
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## ======================= extract features =======================
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##dataset = dataset_list[0]
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#for dataset in dataset_list:
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# print(dataset)
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## make a script file for HCopy
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#hcopy_scp = tempfile.NamedTemporaryFile(mode='w', delete=False)
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#hcopy_scp.close()
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## using the wav_scp in FAME! corpus
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#feature_dir = output_dir + '\\mfc\\' + dataset
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#am_func.make_hcopy_scp_from_filelist_in_fame(FAME_dir, dataset, feature_dir, hcopy_scp.name)
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## extract features
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#subprocessStr = 'HCopy -C ' + config_hcopy + ' -S ' + hcopy_scp.name
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#subprocess.call(subprocessStr, shell=True)
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#os.remove(hcopy_scp.name)
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## ======================= make a list of features =======================
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##dataset = dataset_list[2]
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#for dataset in dataset_list:
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# print(dataset)
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# feature_dir = output_dir + '\\mfc\\' + dataset
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# hcompv_scp = output_dir + '\\scp\\' + dataset + '.scp'
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# am_func.make_filelist(feature_dir, hcompv_scp)
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## ======================= check the phonemes used in the lexicon =======================
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lex_file = FAME_dir + '\\lexicon\\lex.asr'
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phonelist = am_func.get_phonelist(lex_file)
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