def speaker_diarization():
file = '/home/daiab/machine_disk/data/voice_identity/dianxin/1.wav'
use_LDA = False
plot = True
num_speaker = 2
if use_LDA:
pos, cls = aS.speaker_diarization(file,
num_speaker,
mt_size=4.0,
mt_step=0.1,
st_win=0.05,
st_step=0.01,
plot=plot)
else:
pos, cls = aS.speaker_diarization(file, num_speaker, lda_dim=0, plot=plot)
fr, x = audio_basic_io.read_audio_file(file)
sep_voice = [[], []]
pre_pos = 0
cut_num = int(x.shape[0] * 0.0001)
print('cut_num', cut_num)
for i, c in enumerate(cls):
c = int(c)
v_from = pre_pos
v_to = int(pos[i] * fr)
sep_voice[c] += x[v_from + cut_num: v_to - cut_num].tolist()
pre_pos = v_to
print(len(sep_voice[0]), len(sep_voice[1]))
wavfile.write('./0.wav', fr, np.array(sep_voice[0], dtype=np.int16))
wavfile.write('./1.wav', fr, np.array(sep_voice[1], dtype=np.int16))
def speakerDiarizationWrapper(inputFile, numSpeakers, useLDA):
if useLDA:
aS.speaker_diarization(inputFile, numSpeakers, plot_res=True)
else:
aS.speaker_diarization(inputFile,
numSpeakers,
lda_dim=0,
plot_res=True)
def dia(filename, speakers, lda_dim=0):
global labels
file = open('Speaker_Diarization.txt', 'w').close()
main_file(filename, overall=True)
timestamp, classes = speaker_diarization(filename=filename,
n_speakers=speakers,
lda_dim=lda_dim)
file = open('Speaker_Diarization.txt', 'a')
file.write('Timestamp,Classes\n')
for i in range(len(timestamp)):
file.write(f'{timestamp[i]},{int(classes[i])}\n')
file.close()
df = pd.read_csv('Speaker_Diarization.txt')
labels = df['Classes'].unique()
num_labels = len(labels)
previous_label = df['Classes'][0]
sda = dict()
a = []
segments = []
for i in range(df.shape[0]):
if i == 0:
a.append(df['Classes'][i])
a.append(df['Timestamp'][i])
elif df['Classes'][i - 1] == df['Classes'][i]:
a.append(df['Timestamp'][i])
else:
segments.append([a[0], a[1], a[-1]])
a = []
a.append(df['Classes'][i])
a.append(df['Timestamp'][i])
p = []
for label in labels:
for segment in segments:
if segment[0] == label:
p.append([segment[1], segment[2]])
sda[label] = p
p = []
speech = AudioSegment.from_wav(filename)
for key, value in sda.items():
speaker = 0
for parts in value:
speaker += speech[parts[0] * 1000:parts[1] * 1000]
file = filename.split('.')[0] + str('_speaker_') + str(key) + '.wav'
print(speaker)
print(key, value)
if len(value) == 0:
labels = list(labels)
labels.remove(key)
else:
speaker.export(file, format='wav')
print('Files Exported')
main_file(file=file, folder='uploads', labels=labels)