解释代码defrecognize_thread(self): self.max_len=int(self.record_seconds.get()) self.q=queue.Queue(maxsize=2) self.data_deque=deque(maxlen=self.max_len) ifnotself.recognizing: self.recognizing=True self.recognize_real_button.config(text="结束声纹识别") threading.Thread(target=self.recognize_real).start() threading.Thread(target=self.record_real).start() else: self.recognizing=False self.recognize_real_button.config(text="实时声纹识别")
时间: 2023-06-11 21:09:26 浏览: 50
这段代码是一个方法(函数)的定义,名为`recognize_thread`。该方法主要有两个作用:
1. 开始或结束声纹识别
2. 使用多线程同时进行声音录制和声纹识别
具体来说,该方法首先从界面上获取录制时长`self.record_seconds.get()`并将其转换为整数,存储在`self.max_len`中。然后,该方法创建了一个队列(queue)对象`self.q`,用于存储声音数据。同时,该方法还创建了一个双向队列(deque)对象`self.data_deque`,用于存储最近`self.max_len`秒内的声音数据。
接下来,该方法检查是否正在进行声纹识别,如果没有,则将`self.recognizing`设置为True,表示开始进行声纹识别,并将按钮的文本设置为“结束声纹识别”;同时,使用两个线程分别进行声音录制和声纹识别。如果已经在进行声纹识别,则将`self.recognizing`设置为False,表示结束声纹识别,并将按钮的文本设置为“实时声纹识别”。
需要注意的是,该方法中的`self.recognize_real`和`self.record_real`应该是两个不同的方法,分别用于进行声纹识别和声音录制。在该方法中,这两个方法都在不同的线程中运行,以实现同时进行。
相关问题
修改代码使其能辨别出男生和女生,并能进行变声,class Audio_Client(threading.Thread): def __init__(self,ip,port,version): threading.Thread.__init__(self) self.setDaemon(True) self.ADDR = (ip,port) if version == 4: self.sock = socket.socket(socket.AF_INET,socket.SOCK_STREAM) else: self.sock = socket.socket(socket.AF_INET6, socket.SOCK_STREAM) self.p = pyaudio.PyAudio() #音频控件 self.stream = None #音频流 print('音频客户端启动...') print(f'\n音频客户端工作地址:{self.ADDR}') def __del__(self): self.sock.close() if self.stream is not None: self.stream.stop_stream() self.stream.close() self.p.terminate() def run(self): while True: try: self.sock.connect(self.ADDR) break except: time.sleep(3) continue print('音频客户端已经连接...') self.stream = self.p.open(format = FORMAT, channels=CHANNELS, rate=RATE, input=True, frames_per_buffer=CHUNK) while self.stream.is_active(): frames = [] for i in range(0,int(RATE / CHUNK * RECORED_SECONDS)): data = self.stream.read(CHUNK) frames.append(data) senddata = pickle.dumps(frames) try: self.sock.sendall(struct.pack("L",len(senddata))+senddata) except: break
为了辨别男生和女生,并进行变声,您需要对程序进行一些修改。以下是建议修改的代码:
1. 添加文本分类模型
您需要添加一个文本分类模型,可以使用机器学习或深度学习模型训练,用于将语音转换为文本,并将其分类为男性或女性。您可以使用NLTK或Scikit-learn等库来训练和使用这个模型。
2. 添加变声模块
您需要添加一个变声模块,可以使用PyDub库来实现。在文本分类模型将语音分类为男性或女性后,您可以使用PyDub库中的pitch_shift函数来对语音进行变声。具体来说,如果分类结果为男性,则可以将语音的音调调低一些,如果分类结果为女性,则可以将语音的音调调高一些。
修改后的代码如下:
```
class Audio_Client(threading.Thread):
def __init__(self,ip,port,version):
threading.Thread.__init__(self)
self.setDaemon(True)
self.ADDR = (ip,port)
if version == 4:
self.sock = socket.socket(socket.AF_INET,socket.SOCK_STREAM)
else:
self.sock = socket.socket(socket.AF_INET6, socket.SOCK_STREAM)
self.p = pyaudio.PyAudio() #音频控件
self.stream = None #音频流
self.classifier = # 加载文本分类模型
print('音频客户端启动...')
print(f'\n音频客户端工作地址:{self.ADDR}')
def __del__(self):
self.sock.close()
if self.stream is not None:
self.stream.stop_stream()
self.stream.close()
self.p.terminate()
def run(self):
while True:
try:
self.sock.connect(self.ADDR)
break
except:
time.sleep(3)
continue
print('音频客户端已经连接...')
self.stream = self.p.open(format = FORMAT,
channels=CHANNELS,
rate=RATE,
input=True,
frames_per_buffer=CHUNK)
while self.stream.is_active():
frames = []
for i in range(0,int(RATE / CHUNK * RECORED_SECONDS)):
data = self.stream.read(CHUNK)
frames.append(data)
senddata = pickle.dumps(frames)
try:
self.sock.sendall(struct.pack("L",len(senddata))+senddata)
# 将语音转换为文本
text = # 使用语音识别API将语音转换为文本
# 将文本分类为男性或女性
gender = self.classifier.predict(text)
# 对语音进行变声
if gender == 'male':
sound = AudioSegment.from_wav(data)
sound = sound.low_pass_filter(500) # 将音调调低一些
data = sound.export(format='wav')
elif gender == 'female':
sound = AudioSegment.from_wav(data)
sound = sound.high_pass_filter(500) # 将音调调高一些
data = sound.export(format='wav')
except:
break
```
使用QTimer对象代替QBasicTimer对象,修改程序class MyWindow(QWidget): def init(self): super().init() self.thread_list = [] self.color_photo_dir = os.path.join(os.getcwd(), "color_photos") self.depth_photo_dir = os.path.join(os.getcwd(), "depth_photos") self.image_thread = None self.saved_color_photos = 0 # 定义 saved_color_photos 属性 self.saved_depth_photos = 0 # 定义 saved_depth_photos 属性 self.init_ui() def init_ui(self): self.ui = uic.loadUi("C:/Users/wyt/Desktop/D405界面/intelrealsense1.ui") self.open_btn = self.ui.pushButton self.color_image_chose_btn = self.ui.pushButton_3 self.depth_image_chose_btn = self.ui.pushButton_4 self.open_btn.clicked.connect(self.open) self.color_image_chose_btn.clicked.connect(lambda: self.chose_dir(self.ui.lineEdit, "color")) self.depth_image_chose_btn.clicked.connect(lambda: self.chose_dir(self.ui.lineEdit_2, "depth")) def open(self): self.profile = self.pipeline.start(self.config) self.is_camera_opened = True self.label.setText('相机已打开') self.label.setStyleSheet('color:green') self.open_btn.setEnabled(False) self.close_btn.setEnabled(True) self.image_thread = ImageThread(self.pipeline, self.color_label, self.depth_label, self.interval, self.color_photo_dir, self.depth_photo_dir, self._dgl) self.image_thread.saved_color_photos_signal.connect(self.update_saved_color_photos_label) self.image_thread.saved_depth_photos_signal.connect(self.update_saved_depth_photos_label) self.image_thread.start() def chose_dir(self, line_edit, button_type): my_thread = MyThread(line_edit, button_type) my_thread.finished_signal.connect(self.update_line_edit) self.thread_list.append(my_thread) my_thread.start()
以下是使用QTimer对象代替QBasicTimer对象的修改后的代码:
```python
from PyQt5.QtCore import QTimer
class MyWindow(QWidget):
def __init__(self):
super().__init__()
self.thread_list = []
self.color_photo_dir = os.path.join(os.getcwd(), "color_photos")
self.depth_photo_dir = os.path.join(os.getcwd(), "depth_photos")
self.image_thread = None
self.saved_color_photos = 0
self.saved_depth_photos = 0
self.init_ui()
def init_ui(self):
self.ui = uic.loadUi("C:/Users/wyt/Desktop/D405界面/intelrealsense1.ui")
self.open_btn = self.ui.pushButton
self.color_image_chose_btn = self.ui.pushButton_3
self.depth_image_chose_btn = self.ui.pushButton_4
self.open_btn.clicked.connect(self.open)
self.color_image_chose_btn.clicked.connect(lambda: self.chose_dir(self.ui.lineEdit, "color"))
self.depth_image_chose_btn.clicked.connect(lambda: self.chose_dir(self.ui.lineEdit_2, "depth"))
def open(self):
self.profile = self.pipeline.start(self.config)
self.is_camera_opened = True
self.label.setText('相机已打开')
self.label.setStyleSheet('color:green')
self.open_btn.setEnabled(False)
self.close_btn.setEnabled(True)
self.image_thread = ImageThread(self.pipeline, self.color_label, self.depth_label, self.interval, self.color_photo_dir, self.depth_photo_dir, self._dgl)
self.image_thread.saved_color_photos_signal.connect(self.update_saved_color_photos_label)
self.image_thread.saved_depth_photos_signal.connect(self.update_saved_depth_photos_label)
self.image_thread.start()
self.timer = QTimer(self) # 创建QTimer对象
self.timer.timeout.connect(self.update) # 连接timeout信号与槽函数
self.timer.start(100) # 启动定时器,间隔为100ms
def update(self):
# 检查所有的线程是否已完成,并从线程列表中移除已完成的线程
for thread in self.thread_list:
if not thread.isRunning():
self.thread_list.remove(thread)
def chose_dir(self, line_edit, button_type):
my_thread = MyThread(line_edit, button_type)
my_thread.finished_signal.connect(self.update_line_edit)
self.thread_list.append(my_thread)
my_thread.start()
def update_saved_color_photos_label(self, count):
self.saved_color_photos = count
self.ui.label_5.setText(str(self.saved_color_photos))
def update_saved_depth_photos_label(self, count):
self.saved_depth_photos = count
self.ui.label_6.setText(str(self.saved_depth_photos))
```