class HotwordDetector(object): """ Snowboy decoder to detect whether a keyword specified by `decoder_model` exists in a microphone input stream. :param decoder_model: decoder model file path, a string or a list of strings :param resource: resource file path. :param sensitivity: decoder sensitivity, a float of a list of floats. The bigger the value, the more senstive the decoder. If an empty list is provided, then the default sensitivity in the model will be used. :param audio_gain: multiply input volume by this factor. :param apply_frontend: applies the frontend processing algorithm if True. """ def __init__(self, decoder_model, resource=RESOURCE_FILE, sensitivity=[], audio_gain=1, apply_frontend=False): tm = type(decoder_model) ts = type(sensitivity) if tm is not list: decoder_model = [decoder_model] if ts is not list: sensitivity = [sensitivity] model_str = ",".join(decoder_model) self.detector = snowboydetect.SnowboyDetect( resource_filename=resource.encode(), model_str=model_str.encode()) self.detector.SetAudioGain(audio_gain) self.detector.ApplyFrontend(apply_frontend) self.num_hotwords = self.detector.NumHotwords() if len(decoder_model) > 1 and len(sensitivity) == 1: sensitivity = sensitivity * self.num_hotwords if len(sensitivity) != 0: assert self.num_hotwords == len(sensitivity), \ "number of hotwords in decoder_model (%d) and sensitivity " \ "(%d) does not match" % (self.num_hotwords, len(sensitivity)) sensitivity_str = ",".join([str(t) for t in sensitivity]) if len(sensitivity) != 0: self.detector.SetSensitivity(sensitivity_str.encode()) self.ring_buffer = RingBuffer( self.detector.NumChannels() * self.detector.SampleRate() * 5) def start(self, detected_callback=play_audio_file, interrupt_check=lambda: False, sleep_time=0.03, audio_recorder_callback=None, silent_count_threshold=15, recording_timeout=100):

这段代码看起来像是一个热词检测器类的初始化方法。参数包括 `decoder_model`，一个解码器模型文件的路径；`resource`，资源文件的路径；`sensitivity`，一个或多个检测器灵敏度的浮点数；`audio_gain`，音频增益的倍数；`apply_frontend`，是否应用前端处理算法。这个类的实例化会生成一个 SnowboyDetect 对象，用于检测语音流中是否存在指定的关键词。类还包括了一些方法，用于开始检测、回调处理、中断检查等。

相关问题

models = ['lighton.pmdl','lightoff.pmdl','music_on.pmdl','music_off.pmdl'] callbacks = [lambda:callbakck_light_on(), lambda:callbakck_light_off(), lambda:callbakck_music_on(), lambda:callbakck_music_off()] # 定义检测器 signal.signal(signal.SIGINT, signal_handler) sensitivity = [0.5]*len(models) detector = snowboydecoder.HotwordDetector(models, sensitivity=sensitivity) print('开始检测') # 主循环，每隔一段时间检测一次 detector.start(detected_callback=callbacks, interrupt_check=interrupt_callback, sleep_time=0.03) detector.terminate()

这段代码是一个基于Snowboy的热词检测器，可以检测指定的几个热词，当检测到某个热词时，会调用对应的回调函数进行处理。

具体来说，models列表中存储了需要检测的热词模型文件名，callbacks列表中存储了每个热词模型对应的回调函数。在检测器启动后，会不断地检测麦克风输入，当检测到某个热词时，会调用对应的回调函数处理。

其中，sensitivity是一个敏感度列表，用于调整每个模型的检测灵敏度。signal_handler是一个信号处理函数，用于在检测过程中捕获中断信号，以便在程序中止时关闭检测器。interrupt_callback是一个中断回调函数，用于在检测器启动时初始化一些参数，比如设置检测器的最大运行时间。

最后，detector.start()函数启动检测器，detector.terminate()函数在检测结束时终止检测器。

python3 demo.py resources/models/smart_mirror.umdl Traceback (most recent call last): File "/home/pi/snowboy/examples/Python3/demo.py", line 1, in <module> import snowboydecoder File "/home/pi/snowboy/examples/Python3/snowboydecoder.py", line 5, in <module> import snowboydetect File "/home/pi/snowboy/examples/Python3/snowboydetect.py", line 15, in <module> import _snowboydetect ModuleNotFoundError: No module named '_snowboydetect'

看起来你在尝试运行一个使用Snowboy唤醒词检测库的Python脚本，但是出现了一个名为"_snowboydetect"的未找到模块的错误。这通常是因为您需要安装Snowboy的C++库并编译Python绑定才能使用Snowboy的Python库。请确保您已按照Snowboy文档中的说明正确地安装Snowboy，包括编译Python绑定，并且您的Python环境已正确配置。