join(exper_path, 'acoustic_model', 'data', 'wav'),
l_file_tokns, acoustic_feats_path, d_mp_opts)
else:
for file_name_token in l_file_tokns:
feat_extraction(
join(exper_path, 'acoustic_model', 'data', 'wav'),
file_name_token, acoustic_feats_path, d_mp_opts)
# Labels Conversion to Variable Frame Rate:------------------------------------------------
if b_conv_labs_rate and not d_mp_opts[
'b_const_rate']: # NOTE: The script ./script/label_st_align_to_var_rate.py can be also called from comand line directly.
label_state_align = join(exper_path, 'acoustic_model', 'data',
'label_state_align')
label_state_align_var_rate = pars_acous_train['Labels']['label_align']
fs = int(pars_acous_train['Waveform']['samplerate'])
ltvr.convert(file_id_list, label_state_align, acoustic_feats_path, fs,
label_state_align_var_rate)
# Run duration training:-------------------------------------------------------------------
if b_dur_train:
call([
submit_path, run_merlin_path,
join(dur_model_conf_path, 'dur_train.conf')
])
# Run acoustic train:----------------------------------------------------------------------
if b_acous_train:
call([
submit_path, run_merlin_path,
join(acous_model_conf_path, 'acous_train.conf')
])
if b_feat_extr:
# Extract features:
lu.mkdir(acoustic_feats_path)
if b_feat_ext_multiproc:
lu.run_multithreaded(feat_extraction, join(exper_path, 'acoustic_model', 'data', 'wav'), l_file_tokns, acoustic_feats_path, d_mp_opts)
else:
for file_name_token in l_file_tokns:
feat_extraction(join(exper_path, 'acoustic_model', 'data', 'wav'), file_name_token, acoustic_feats_path, d_mp_opts)
# Labels Conversion to Variable Frame Rate:------------------------------------------------
if b_conv_labs_rate and not d_mp_opts['b_const_rate']: # NOTE: The script ./script/label_st_align_to_var_rate.py can be also called from comand line directly.
label_state_align = join(exper_path, 'acoustic_model', 'data', 'label_state_align')
label_state_align_var_rate = pars_acous_train['Labels']['label_align']
fs = int(pars_acous_train['Waveform']['samplerate'])
ltvr.convert(file_id_list,label_state_align, acoustic_feats_path, fs, label_state_align_var_rate)
# Run duration training:-------------------------------------------------------------------
if b_dur_train:
call([submit_path, run_merlin_path, join(dur_model_conf_path, 'dur_train.conf')])
# Run acoustic train:----------------------------------------------------------------------
if b_acous_train:
call([submit_path,run_merlin_path, join(acous_model_conf_path, 'acous_train.conf')])
# Run duration syn:------------------------------------------------------------------------
if b_dur_syn:
call([submit_path, run_merlin_path, join(dur_model_conf_path, 'dur_synth.conf')])
# Run acoustic synth:----------------------------------------------------------------------
if b_acous_syn: