#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))
print "speaker ", cluster.get_best_speaker()
print "get_basename ",seg.get_basename()
print "\n\n"
print
print "RND"
if True:
print "=============SHELVE================"
sdb= shelve.open(FILE_PATH+"_shelve")
tmp_sdb={}
"""
db = GMMVoiceDB(DB_PATH)
v = Voiceid(db, FILE_PATH)
v.extract_speakers()
"""
for c in v.get_clusters():
cluster = v.get_cluster(c)
print "", cluster._label, " cluster.get_best_five()[0][0]=", cluster.get_best_five()[0][0], " cluster.get_distance()=", cluster.get_distance(), " cluster.get_distance()>SCORE", cluster.get_distance()<SCORE
speaker="Unknown"
if cluster.get_distance()>SCORE:
speaker=cluster.get_best_five()[0][0]
sp0=cluster.get_best_five()[0][0]
sp1=cluster.get_best_five()[0][1]
if sp0.startswith(sp1[0:-1]) or sp1.startswith(sp0[0:-1]):
speaker=cluster.get_best_five()[0][0]
list_seg=cluster.get_segments()
for seg in list_seg:
tmp_sdb[seg.get_start()]=[str(speaker),str( humanize_time( (float(seg.get_end())-float(seg.get_start())) / 100) ),str( humanize_time(float(seg.get_end()) / 100) ), str( humanize_time(float(seg.get_start()) / 100) )]
tmp_sdb_keys=tmp_sdb.keys()
tmp_sdb_keys.sort()
for k in tmp_sdb_keys:
sdb[str(k)]=tmp_sdb[k]
sdb.sync()
print " start = ", str(k), " data=", sdb[str(k)]
sdb.close()
print "RND"
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)
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()))
