def do_IS_speakers():
output = []
Productions = ['2','3']
for w in Words:
mod_path = os.path.join(MODEL_DIR,'modeltalker_%s.wav' %w)
mod_env = calc_envelope(mod_path,**opt_dict)
print(w)
for s in Speakers:
if 'IS' not in s:
continue
if s == 'modeltalker':
continue
sp = s.split('_')[0]
s_dir = os.path.join(JAM_DIR,s)
for p in Productions:
base_path = os.path.join(s_dir,'%s_%s1is.wav' % (sp,w))
shad_path = os.path.join(s_dir,'%s_%s%sis.wav' % (sp,w,p))
if not os.path.isfile(base_path):
continue
if not os.path.isfile(shad_path):
continue
base_env = calc_envelope(base_path,**opt_dict)
shad_env = calc_envelope(shad_path,**opt_dict)
b_to_m_sim = envelope_match(mod_env,base_env)
s_to_m_sim = envelope_match(mod_env,shad_env)
output.append([sp,p,w,b_to_m_sim,s_to_m_sim])
with open(os.path.join(BASE_DIR,'jam_output8IS.txt'),'w') as f:
csvw = csv.writer(f,delimiter='\t')
csvw.writerow(['Shadower_number','Block',
'Word','base_to_mod_env_sim','shad_to_mod_env_sim',
#'mfcc_shad_to_mod','mfcc_mod_to_shad',
#'spec_shad_to_mod','spec_mod_to_shad',
#'mfcc_base_to_mod','mfcc_mod_to_base',
#'spec_base_to_mod','spec_mod_to_base'
])
for l in output:
csvw.writerow(l)
def token_to_env(wt):
path = fetch_temp_resource('buckeye-wt-%d.wav' % wt.pk)
if not os.path.isfile(path):
extract_vowel(wt.get_dialog_path(),wt.Begin,wt.End,path)
env = calc_envelope(path)
return env
