Ejemplo n.º 1
0
def set_name(device_id, voice_path, new_name):
    print "set " + voice_path + " to: " + new_name
    new_name = new_name.replace(' ', '')
    if not new_name.isalnum():
        print 'error: SPEAKER_ID must be alphanumeric'
        return
    if new_name in db.get_speakers()['U'] or new_name in db.get_speakers(
    )['M'] or new_name in db.get_speakers()['F']:
        voice = Voiceid(db, voice_path, single=True)
        voice.extract_speakers(quiet=True, thrd_n=3)

        cluster = voice.get_cluster('S0')
        cluster.set_speaker(new_name)
        voice.update_db()
        return
    try:
        # assume only one speaker in one sample
        ww = fm.file2wav(voice_path)
        file_basename, extension = os.path.splitext(ww)

        db.add_model(file_basename, new_name)
        os.remove(file_basename + ".seg")
        os.remove(file_basename + ".ident.seg")
        os.remove(file_basename + ".init.gmm")
    except IOError:
        print "voice file doesn't exist"
    except OSError:
        print "WARNING: error deleting some intermediate files"
    except TypeError:
        print "Type error"
Ejemplo n.º 2
0
def segment_input(wavfile, dbpath='./voicedb'):
	db = GMMVoiceDB(dbpath)
	v = Voiceid(db, wavfile)
	v.extract_speakers()
	
	speaker_clusters={}
	
	for c in v.get_clusters():
		cluster = v.get_cluster(c)
		print cluster
		cluster.print_segments()
		print
Ejemplo n.º 3
0
def voicerec(fname):
	db = GMMVoiceDB('models')
	v = Voiceid(db,fname)
	v.extract_speakers()
	txt=''
	for c in v.get_clusters():
	    cl= v.get_cluster(c)
	    cluster=str(cl)
	    cluster=cluster.split(' ')
	    cluster=cluster[1]
	    cluster=cluster.strip('(')
	    cluster=cluster.strip(')')
	    txt=txt+'Speaker : '+cluster
	    seg=str(cl.print_segments())
	    txt=txt+'\n'+seg
	out.insertPlainText(txt+"\n")
Ejemplo n.º 4
0
def voicerec(fname):
    db = GMMVoiceDB('models')
    v = Voiceid(db, fname)
    v.extract_speakers()
    txt = ''
    for c in v.get_clusters():
        cl = v.get_cluster(c)
        cluster = str(cl)
        cluster = cluster.split(' ')
        cluster = cluster[1]
        cluster = cluster.strip('(')
        cluster = cluster.strip(')')
        txt = txt + 'Speaker : ' + cluster
        seg = str(cl.print_segments())
        txt = txt + '\n' + seg
    out.insertPlainText(txt + "\n")
Ejemplo n.º 5
0
def recognize(device_id, voice_path):
    # voice_db_lock.acquire()
    print db.get_speakers()
    # assume only one speaker in one sample, To Do: multiple speakers in one sample
    # set to True to force to avoid diarization, in case a single speaker in the file
    try:
        voice = Voiceid(db, voice_path, single=True)
        # extract_speakers(interactive=False, quiet=False, thrd_n=1)
        voice.extract_speakers(quiet=True, thrd_n=3)
        # clusters = voice.get_clusters()
        cluster = voice.get_cluster('S0')
        # speaker = cluster.get_best_speaker()
        speaker = "unknown"
        speakers = cluster.get_best_five()
        if len(speakers) > 0:
            value = speakers[0][1]
            if value > -33.0:
                speaker = speakers[0][0]
        # speaker = cluster.get_speaker()

        print speaker
        payload = {
            'audio': 'http://52.24.205.33/voice/' + voice_path,
            'userName': speaker,
            'time': '1'
        }
        requests.post('http://129.236.234.21:8080/message',
                      data=json.dumps(payload),
                      headers=HEADERS)
        client.publish("ais/recognize/result/" + device_id + "/" + voice_path,
                       speaker)
        os.remove(voice.get_file_basename() + '.seg')
        os.remove(voice.get_file_basename() + '.g.seg')
        os.remove(voice.get_file_basename() + '.s.seg')
        w = voice.get_file_basename() + '.wav'
        if voice.get_filename() != w:
            os.remove(w)
        shutil.rmtree(voice.get_file_basename())
    except IOError:
        print "voice file doesn't exist"
Ejemplo n.º 6
0
def GetSpeakers(voicedb, audiofile):
    from voiceid.sr import Voiceid
    from voiceid.db import GMMVoiceDB
    import logger
    try:
        v = Voiceid(voicedb, audiofile)
    except:
        logger.write("e", "File: voicehandler.py | Function: GetSpeakers | Error: Could not call Voiceid constructor!")
        return False
    try:
        v.extract_speakers()
    except:
        logger.write("e", "File: voicehandler.py | Function: GetSpeakers | Error: Could not extract speakers from file!")
        return False
    try:
        for c in v.get_clusters():
            cluster = v.get_cluster(c)
            voicedb.set_maxthreads(5)
    except:
        logger.write("e", "File: voicehandler.py | Function: GetSpeakers | Error: Could not get clusters!")
        return False
    return cluster
Ejemplo n.º 7
0
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!'
Ejemplo n.º 8
0
Archivo: test1.py Proyecto: crs4/ACTIVE
 #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.extract_speakers()
 
 for c in v.get_clusters():
     #print "c ", c   
     cluster = v.get_cluster(c) 
     """
     print "cluster.get_name ", cluster.get_name()        
     print "cluster.get_best_speaker ", cluster.get_best_speaker()
     print "cluster.get_duration ", cluster.get_duration()
     print "cluster.to_dict ", cluster.to_dict()
     print "cluster.get_segments ", cluster.get_segments()
     cluster.print_segments()
     #cluster.print_segments()
     """
     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:
         print "start %s stop %s" %  (humanize_time(float(seg.get_start()) / 100),  humanize_time(float(seg.get_end()) / 100))
Ejemplo n.º 9
0
from voiceid.sr import Voiceid
from voiceid.db import GMMVoiceDB
import sys

#   create voice db

db = GMMVoiceDB('voiceDB')

print "DB Models:"
print db.get_speakers()

v = Voiceid(db, sys.argv[1])

v.extract_speakers(False, True)

# Set cluster speaker
c = v.get_cluster('S1')
c.set_speaker('derek')

c = v.get_cluster('S6')
c.set_speaker('derek')

# update db
v.update_db()
print "DB Models:"
print db.get_speakers()
Ejemplo n.º 10
0
def test_dir():
    all_wav = []
    for f in os.listdir(DIR_PATH):
        if fnmatch.fnmatch(f, "*.wav") and f.find("##") > -1:
            all_wav.append(f)
    all_wav = verify_goodness(all_wav)
    print all_wav
    print "verifica ok... procediamo"

    logging.basicConfig(filename=DIR_PATH + "/result.log", level=logging.INFO)

    db = GMMVoiceDB("/Users/labcontenuti/.voiceid/gmm_db")
    # filter_criteria="Fabrizio_Gifuni##02Pasticciaccio.wav"
    for wav in all_wav:
        # if wav.find(filter_criteria)>-1:
        print "--------------------" + wav + "------------------------"
        v = Voiceid(db, DIR_PATH + wav)
        v.extract_speakers()

        logging.info("\n\n\n---------------------" + wav + "------------------")
        wav_tostring = str(wav) + ";   "

        for c in v.get_clusters():
            cluster = v.get_cluster(c)
            for seg in cluster.get_segments():
                print "\n seg: ", seg
                print seg.get_start()
                print seg.get_end()
                print humanize_time(seg.get_duration())

            print "cluster.get_duration  ", cluster.get_duration()
            logging.info("duration: " + str(cluster.get_duration()))
            wav_tostring = wav_tostring + ":  " + "duration:" + str(cluster.get_duration())

            print "cluster.get_name ", cluster.get_name()
            print "cluster.get_best_speaker ", cluster.get_best_speaker(), " correct?", verify_speaker(
                wav, cluster.get_best_speaker()
            )
            logging.info("best_speaker " + str(cluster.get_best_speaker()))
            wav_tostring = wav_tostring + ";  " + "best_speaker:" + str(cluster.get_best_speaker())

            print "v._get_time() ", v._get_time(), " ", humanize_time(v._get_time())
            logging.info("get_time:  " + str(humanize_time(v._get_time())))
            wav_tostring = wav_tostring + ";  " + "get_time:" + str(humanize_time(v._get_time()))

            # if cluster.get_best_speaker()=="unknown":
            print "cluster.get_best_five ", cluster.get_best_five(), cluster.get_best_five()[0]
            logging.info("best of five: " + str(cluster.get_best_five()[0]))
            wav_tostring = wav_tostring + ";  " + "best of five:" + str(cluster.get_best_five()[0])

            print "cluster.get_distance() ", str(cluster.get_distance())
            logging.info("distance best-closest " + str(cluster.get_distance()))
            wav_tostring = wav_tostring + ";  " + "distance best-closest:" + str(cluster.get_distance())

            print
            if not cluster.get_best_speaker() == "unknown":
                if verify_speaker(wav, cluster.get_best_speaker()):
                    find_ok.append(wav_tostring)
                else:
                    find_errata.append(wav_tostring)
            else:
                not_find.append(wav_tostring)
                if verify_speaker(wav, cluster.get_best_five()[0][0]):
                    unknown_ok.append(wav_tostring)
                else:
                    unknown_errata.append(wav_tostring)

        print "Number TEST--" + str(len(find_ok) + len(find_errata) + len(not_find))
        print "OK---------  " + str(len(find_ok))
        print "ERRATA-------" + str(len(find_errata))
        print "UNKNOWN------" + str(len(not_find))
        print "UNKNOWN ERR--" + str(len(unknown_errata))
        print "UNKNOWN  OK--" + str(len(unknown_ok))
    # resutl_file=file(DIR_PATH+"result.txt", "a+")

    logging.info("\n\n")  # for wav in unknown_errata:
    logging.info("Number TEST " + str(len(find_ok) + len(find_errata) + len(not_find)))
    logging.info("ok " + str(len(find_ok)))
    logging.info("ERRATA" + str(len(find_errata)))
    logging.info("UNKNOWN" + str(len(not_find)))
    logging.info("UNKNOWN ERR " + str(len(unknown_errata)))
    logging.info("UNKNOWN  OK " + str(len(unknown_ok)))

    logging.info("\n\n\n----UNKNOWN  OK ---")
    for f in unknown_ok:
        logging.info(f)

    logging.info("\n\n\n----UNKNOWN  ERRATA ---")
    for f in unknown_errata:
        logging.info(f)

    logging.info("\n\n\n----ERRATA---")
    for f in find_errata:
        logging.info(f)
Ejemplo n.º 11
0
#Using voiceid(google opensource project) for voice recognisation using python
from voiceid.sr import Voiceid          
from voiceid.db import GMMVoiceDB
db = GMMVoiceDB('mydir')                #creating database/directory of registered voices
db.add_model('C:\Users\raman\Documents\raman.wma', 'Raman','M')
db.add_model('C:\Users\raman\Documents\lalit.wma', 'Lalit','M')
db.add_model('C:\Users\raman\Documents\aneesha.wma', 'Aneesha','F')
db.add_model('C:\Users\raman\Documents\priyanka.wma', 'Priyanka','F')
db.get_speakers()  # this will get all the speakers in the database/directory
if(db.matchvoice('C:\Users\raman\Documents\lalit.wma', 'Lalit'))   #the matchvoice function will compare the voices
{
  print "Lalit is present" }
  else print "Lalit is absent"

v = Voiceid(db)
v.extract_speakers()
for c in v.get_clusters():
   cluster = v.get_cluster(c)
   print cluster 
cluster.print_segments()