def main():
if len(argv) != 4:
exit("Usage: SoundPrintCollector.py <dict> <config> <output-folder>")
num_repeat_key = 'NUMREPEAT'
# Get configuration
num_repeat = ParseConfig(CONFIG_DIR + argv[2] + '.conf', num_repeat_key)
if num_repeat != '':
num_repeat = int(num_repeat)
else:
num_repeat = 1
words, model_id = GetDictionary(DICT_DIR + argv[1] + '.txt')
total_num = len(words) * num_repeat
OUTPUT_DIR = TRAIN_DIR + argv[3] + '/'
if not isdir(OUTPUT_DIR):
mkdir(OUTPUT_DIR)
# Collect sound print for single model
for i in range(len(words)):
for k in range(num_repeat):
total_num -= 1
print(str(total_num) + ' transcript(s) remaining.')
if words[i].find('!') > -1:
instruction = 'Press <Enter> to record background noise.\n' + words[
i]
else:
instruction = 'Get ready to speak the following script and press <Enter> to start record.\n' + words[
i] + '\n Remember to leave 3 seconds of blank before and after the utterance.\n'
Collect(OUTPUT_DIR + model_id[i] + '-' + str(k) + '.wav',
instruction)
print('Done\a')
import numpy as np
from x64.Release.TrainCore import VDecode
from glob import glob
from pdb import set_trace
from os import getcwd
MAIN_DIR = getcwd() + '/'
MFCC_FOLDER = MAIN_DIR + 'mfcc/single/'
MODEL_FOLDER = MAIN_DIR + 'model/'
DICT_DIR = MAIN_DIR + 'dict/'
CONFIG_DIR = MAIN_DIR + 'config/'
# Get iteration time limit from config
# Get configuration
conf_filename = CONFIG_DIR + sys.argv[2] + '.conf'
max_iter = int(ParseConfig(conf_filename, 'MAXITER'))
#########################################################################
# MAIN ENTRY #
#########################################################################
if len(sys.argv) < 3:
sys.exit("Usage: Decoder.py <dict> <config>")
words, model_id = GetDictionary(DICT_DIR + sys.argv[1] + '.txt')
models = []
for k in range(len(model_id)):
# Load model
model_filename = MODEL_FOLDER + model_id[k] + '.xml'
name, states, num_states, num_components, dim_observation, log_trans, log_coef, mean, log_var = ReadModel(
model_filename)
#########################################################################
# MAIN ENTRY #
#########################################################################
if len(argv) != 4:
exit("Usage: ModelIitializer.py <dict> <config> <mfcc-dir>")
MFCC_FOLDER = MAIN_DIR + 'mfcc/train/'+argv[3]+'/'
words, model_id = GetDictionary(DICT_DIR + argv[1] + '.txt')
num_components_key = 'NUMCOMPONENTS'
num_repeat_key = 'NUMREPEAT'
# Get configuration
conf_filename = CONFIG_DIR + argv[2] + '.conf'
num_components = ParseConfig(conf_filename, num_components_key)
num_repeat = ParseConfig(conf_filename, num_repeat_key)
if num_components != '':
num_components = int(num_components)
else:
# Use only 1 component in GMM by default
num_components = 1
if num_repeat != '':
num_repeat = int(num_repeat)
else:
num_repeat = 1
# For each model
for k in range(len(model_id)):
# Load MFCC data
# To compute the global mean and log_var
#########################################################################
if len(argv) != 3:
exit("Usage: ModelCreator.py <dict> <config>")
dict_file = open(DICT_DIR + argv[1] + '.txt')
tokens_list = []
for line in dict_file:
tokens_list.append(line.strip().split())
dict_file.close()
num_subphones_key = 'NUMSUBPHONES'
# Get configuration
num_subphones = int(ParseConfig(CONFIG_DIR + argv[2] + '.conf',num_subphones_key))
for tokens in tokens_list:
ID = tokens[0]
name = tokens[1]
states = ['<START>']
for i in range(3, len(tokens)):
for k in range(num_subphones):
states.append('<' + tokens[i] + str(k)+'>')
states.append('<END>')
num_states = len(states)
# Get flat start log transition matrix
row_idx = get_row_idx(num_states)