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zcr_test.py
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# encoding=utf-8
import random
import numpy as np
from pyaudio import PyAudio
from convert_wav_plus import ZCR
from configure_class import Configure
from speech_recognition import Recognition
import matplotlib.pyplot as plt
def save_wav(filename,binary_str):
c = Configure
wf = wave.open(filename, 'wb')
wf.setnchannels(c.CHANNELS)
wf.setsampwidth(pyaudio.get_sample_size(c.FORMAT))
wf.setframerate(c.RATE)
wf.writeframes(binary_str)
wf.close()
def recoder_and_decide(unit_time=0.3):
pa = PyAudio()
config = Configure(unit_time=unit_time)
times = 0
result_before = []
binary_str = b""
pre_str = b""
temp_binary_str = b""
print("begin_____________________")
is_recording,pre_is_recording = False, False
test_zcr_count = 0
while times < 100 or True:
stream = pa.open(format=config.FORMAT,
channels=config.CHANNELS,
rate=config.RATE,
input=True,
frames_per_buffer=config.CHUNK)
frames = []
times += 1
pre_is_recording = is_recording
pre_str = temp_binary_str
stream.start_stream()
for i in range(0, config.get_count_chunk()):
data = stream.read(config.CHUNK)
frames.append(data)
stream.stop_stream()
temp_binary_str = b''.join(frames)
digit_data = np.fromstring(temp_binary_str, np.int16)
zcr = ZCR(digit_data)
zcr_flag,energy_flag = zcr.get_weather_start_record_state()
is_recording = energy_flag or zcr_flag
# is_recording = zcr_flag or energy_flag
print(zcr_flag,energy_flag)
if zcr_flag:
test_zcr_count += 1
# print("zcr_rate = {},max_energy = {}".format(max(zcr_rate),max(energy)))
# zcr_flag = max(zcr_rate) > zcr.zcr_threshold
# energy_flag = max(energy) > zcr.energy_threshold
# print("max_zcr={},max_energy={}".format(max(zcr_rate),max(energy)))
# print("t={}s,z={},e={}".format(times*config.RECORD_SECONDS,zcr_flag,energy_flag))
# if zcr_flag or energy_flag:
# is_recording = True
# else
# is_recording = False
# result_before += list(digit_data)
if is_recording:
# print(type(binary_str),type(temp_binary_str))
if not pre_is_recording:
binary_str = pre_str
binary_str += temp_binary_str
print("Recording,time=%s" % str(len(binary_str)/32000))
print("\n__________________________________________")
# print("Recording@@@{}@@@{}".format(zcr_flag,energy_flag))
elif pre_is_recording:
# stop recording and start recognizing
print("test_zcr_count = %d" % test_zcr_count)
test_zcr_count = 0
print("Recognizing......")
sp = Recognition('./969_914.pb', './conv_labels.txt')
recognized_dict = sp.run(binary_str,unit_time)
print("识别结果：{}".format(recognized_dict))
binary_str = b""
else:
print("Finding")
# print("Finding+++{}+++{}".format(zcr_flag,energy_flag))
stream.stop_stream()
stream.close()
pa.terminate()
return None
result = recoder_and_decide(0.35)
# plt.subplot(211)
# plt.plot(list(range(len(result))),result)
# plt.subplot(212)
# plt.plot(list(range(len(result_before))),result_before)
# z = ZCR(r,unit_samples=64)
# zcr,energy = z.calc_zcr_and_energy()
# zcr_diff = []
# zcr_float = []
# for i in range(len(zcr)-1):
# zcr_float.append(float(zcr[i])/64)
# zcr_diff.append(zcr[i+1]-zcr[i])
# print(zcr)
# plt.subplot(411)
# plt.plot(list(range(len(zcr))),zcr)
# plt.subplot(412)
# plt.plot(list(range(len(r))),r)
# plt.subplot(413)
# plt.plot(list(range(len(zcr_diff))),zcr_diff)
# plt.subplot(414)
# plt.plot(list(range(len(z.energy))),z.energy)
plt.show()