def speaker_recog_thread(outLabel):
global d
global On
while True:
try:
g = q.get()
now, file_name, data = g
now_s = str(now)
# if not on:
# _, speaker = predict_speaker(file_name)
# outLabel.config(text=speaker)
# print(now_s, speaker)
# if speaker in target_speakers:
# on = 1
# else:
google_ans = google_stt(file_name)
D = np.frombuffer(data, dtype=np.int16)
data = librosa.core.resample(
1.0 * D, orig_sr=16000,
target_sr=8000).astype(dtype=np.int16).tobytes()
systran_ans = asr(data)
if google_ans or systran_ans:
outLabel.config(text="Google : " + google_ans + '\r\n' +
"엘솔루 : " + systran_ans)
else:
print("empty")
# On = True
# on -= 1
# outLabel.config(text=speaker + ': ' + out)
# print(speaker, out)
except queue.Empty:
continue
def speech_recog_thread():
global d
while True:
try:
g = q.get()
now, data = g
now_s = str(now)
out = asr(data)
print(out)
except queue.Empty:
continue
def asr_thread():
while True:
try:
g = q2.get()
now, file_name, data, speaker = g
D = np.frombuffer(data, dtype=np.int16)
data = librosa.core.resample(1.0 * D, orig_sr=16000, target_sr=8000).astype(dtype=np.int16).tobytes()
speech = asr(data)
if speech:
if speech in CESLeA:
speech = "CESLeA"
# print(speaker, speech)
post.post(createdAt=now, speaker=speaker, speakerId=speaker, content=speech)
else:
# print("empty")
except queue.Empty:
continue
def asr_thread(outLabel):
global speaker
global count
while True:
g = q2.get()
if count:
now, data = g
now_s = str(now)
if len(data) < 0.5 * 16000 * 2:
continue
D = np.frombuffer(data, dtype=np.int16)
data = librosa.core.resample(
1.0 * D, orig_sr=16000,
target_sr=8000).astype(dtype=np.int16).tobytes()
print('run asr')
out = asr(data)
if out:
count = count - 1
print(out)
outLabel.config(text=spk[speaker] + ': ' + out)
else:
print('out is empty')
def speaker_recog_thread(outLabel):
global d
# on = 0
while True:
try:
g = q.get()
now, file_name, data = g
now_s = str(now)
_, speaker = predict_speaker(file_name)
outLabel.config(text=speaker)
print(now_s, speaker)
D = np.frombuffer(data, dtype=np.int16)
data = librosa.core.resample(
1.0 * D, orig_sr=16000,
target_sr=8000).astype(dtype=np.int16).tobytes()
out = asr(data)
if out:
outLabel.config(text=speaker + ': ' + out)
print(speaker, out)
else:
print("empty")
pass
except queue.Empty:
continue