def main():
parser = argparse.ArgumentParser(version="1.0", prog="Voice Recognition")
parser.add_argument("-a", "--add", action="store_true", help="Add a new source")
parser.add_argument("audio", type=str, help="Name of the audio file (*.wav)")
args = parser.parse_args()
audio = HOME_FOLDER + args.audio
db = GMMVoiceDB(HOME_FOLDER)
if args.add:
name = str(time.strftime("%d%m%Y%H%M%S"))
db.add_model(audio.split(".")[0], name)
else:
v = Voiceid(db, audio)
v.diarization()
dic = db.get_speakers()
dist = []
d2u = {}
for gender in dic:
users = dic[gender]
for u in users:
dist.append(db.match_voice(audio, u, gender)[u])
d2u[dist[-1]] = u
dist.sort(None, None, True)
if (dist[0] - dist[1] + CEIL) > EPS:
return d2u[dist[0]]
else:
return "unkonwn"
def main():
parser = argparse.ArgumentParser(version='1.0',prog='Voice Recognition')
parser.add_argument("-a", "--add", action="store_true", help="Add a new source")
parser.add_argument("audio", type=str, help="Name of the audio file (*.wav)")
args = parser.parse_args()
audio = HOME_FOLDER+args.audio
db = GMMVoiceDB(HOME_FOLDER)
if args.add:
print('Adding User...')
name = str(time.strftime("%d%m%Y%H%M%S"))
db.add_model(audio.split('.')[0], name)
print('User '+name+' Added!')
else:
print('Recognition...')
v = Voiceid(db, audio)
v.diarization()
dic = db.get_speakers()
dist = []
d2u = {}
for gender in dic:
users = dic[gender]
#print('Gender: ',gender)
for u in users:
#print(db.match_voice(audio, u, gender))
dist.append(db.match_voice(audio, u, gender)[u])
d2u[dist[-1]]=u
dist.sort(None, None, True)
if (dist[0]-dist[1]+CEIL)>EPS :
print(d2u[dist[0]])
else:
print('unkonwn')
print "Done!"
def recognition():
global audio, db, label
if audio != None:
print 'Comparing...'
#dic = db.get_speakers()
v = Voiceid(db, audio+'.wav')
#v.extract_speakers()
v.diarization()
dic = db.get_speakers()
dist = []
d2u = {}
for gender in dic:
users = dic[gender]
print('Gender: ',gender)
for u in users:
print(db.match_voice(audio+'.wav', u, gender))
dist.append(db.match_voice(audio+'.wav', u, gender)[u])
d2u[dist[-1]]=u
print('--------------')
print("Best Speaker (Own)")
dist.sort(None, None, True)
print( (dist[0]-dist[1]+CEIL),EPS,dist )
if (dist[0]-dist[1]+CEIL)>EPS :
print(d2u[dist[0]])
#print(dic)
print('--------------')
print("Best Speaker")
print("Audio: ",audio.split('/')[-1])
v.extract_speakers(False, True)
for c in v.get_clusters():
cluster = v.get_cluster(c)
print(cluster.get_best_speaker() )
print('------------')
'''
print 'Comparing...'
v = Voiceid(db, audio+'.wav')
#s = StringIO.StringIO()
#with s as sys.stdout:
v.extract_speakers(False, True)
#with open('output.txt','w') as sys.stdout:
for c in v.get_clusters():
cluster = v.get_cluster(c)
user = cluster.get_best_speaker()
print('------------')
if user != "unknown":
print("Best Speaker: %s" % (user) )
print("Speaker: %s" % (cluster.get_speaker()) )
print("Gender: %s" % (cluster.get_gender()) )
print("Distance: %s" % (cluster.get_distance()) )
print("Mean: %s" % (cluster.get_mean()) )
print("Dist. from mean: %s" % (cluster.get_m_distance()) )
print("Best five speakers: " % (cluster.get_best_five()) )
else:
print("User Unknown")
print("Gender: %s" % (cluster.get_gender()) )
print("Distance: %s" % (cluster.get_distance()) )
print("Best five speakers: " % (cluster.get_best_five()) )
print('------------')
#sys.stdout = sys.__stdout__
#labelB["text"] = "Users: " + str(listName)'''
print "Done!"
else :
print 'Record audio first!'
#v = Voiceid(db, '../Test_set_all/Monica-Bellucci-interview.mp3')
#v = Voiceid(db, '../Test_set_all/Pasolini1971.mp3')
#v = Voiceid(db, '/home/felix/Desktop/u/facciamoiconti.mp3')
#v = Voiceid(db, '/home/felix/Desktop/u/facciamoiconti/S32.wav')
#v = Voiceid(db, '/Users/labcontenuti/Desktop/voiceid/adaltavoce/voci/FabrizioGifuni-promessisposi-p1.wav')
#v = Voiceid(db, '/Users/labcontenuti/Desktop/voiceid/adaltavoce/test/Piero_Baldini##mobyDick01_1sec.wav')
#v = Voiceid(db, '/Users/labcontenuti/Desktop/voiceid/adaltavoce/test/Piero_Baldini##mobyDick01_3sec.wav')
#v = Voiceid(db, '/Users/labcontenuti/Desktop/voiceid/DataSetVideolinaVoci/Giacomo_Mameli/2/Giacomo_Mameli##1-1.wav')
v = Voiceid(db, '/Users/labcontenuti/Documents/workspace/activevoice/audio_test/2sec.wav')
#v = Voiceid(db, '/Users/labcontenuti/Desktop/voiceid/DataSetVideolina_FIC02/Fadda_Paolo/Paolo_Fadda##6-30s.wav')
#v = Voiceid(db, '//Users/labcontenuti/Music/facciamo_i_conti_internet.wav')
v.diarization()
print v
v.extract_cluster()
print v.get_clusters()
exit()
v.extract_speakers_without_diarization()
#v.extract_speakers()
for c in v.get_clusters():
#print "c ", c
cluster = v.get_cluster(c)
print "cluster.wave ", cluster.wave
print "cluster.get_name ", cluster.get_name()
print "\n\n\n\n\n\n"
list_seg=cluster.get_segments()
for seg in list_seg:
