（1）去趋势项（如直流电流），并将数据归一化到区[0, 1]；（2）进行多级小波分解；（3）使用步骤...
首先,确保已安装所需的库: pipinstall pyaudiopipinstall pydubpipinstall noisereduce 接下来,创建一个名为audio_noise_reduction.py的Python文件,并将以下代码粘贴到其中: importpyaudiofrompydubimportAudioSegmentfromnoisereduceimportreduce_noiseimportnumpyasnpCHUNK=1024FORMAT=pyaudio.paInt16CHANNELS=1RATE=44100RECOR...
以下是一个使用AudioSegment去除音频噪音的示例代码: frompydubimportAudioSegment# 读取音频文件audio=AudioSegment.from_file("input_audio.mp3")# 去除噪音# 注意:这里的 noise_reduction 参数需要根据实际情况调整clean_audio=audio.reduce_noise()# 保存处理后的音频clean_audio.export("output_audio.mp3",format="mp...
sample_rate=librosa.load(file_path,sr=None)# 去除底噪reduced_noise_signal=nr.reduce_noise(y=audio_signal,sr=sample_rate)# 保存去噪后的音频文件output_file_path='output_audio.wav'# 输出的音频文件路径write(output_file_path,sample_rate,reduced_noise...
import noisereduce as nr # load data rate, data = wavfile.read("mywav.wav") # select section of data that is noise noisy_part = data[10000:15000] # perform noise reduction reduced_noise = nr.reduce_noise(audio_clip=data, noise_clip=noisy_part, verbose=True) ...
Steps of the Stationary Noise Reduction algorithm A spectrogram is calculated over the noise audio clip Statistics are calculated over spectrogram of the the noise (in frequency) A threshold is calculated based upon the statistics of the noise (and the desired sensitivity of the algorithm) ...
def save_STFT(文件、名称、活动、主题):#read音频数据audio_data,sample_rate =librosa.load(文件)打印(文件) 代码语言:javascript 复制 #noise reduction noisy_part = audio_data[0:25000] reduced_noise = nr.reduce_noise(audio_clip=audio_data, noise_clip=noisy_part, verbose=False) #trimming trimmed...
pip install noisereduce 编写降噪代码: from scipy.io import wavfile import noisereduce as nr # load data rate, data = wavfile.read("./output/test/vocals.wav") # perform noise reduction reduced_noise = nr.reduce_noise(y=data, sr=rate) wavfile.write("./output/test/vocals.wav", rate, ...
这里使用noisereduce来进行降噪: pip install noisereduce 编写降噪代码: from scipy.io import wavfile import noisereduce as nr # load data rate, data = wavfile.read("./output/test/vocals.wav") # perform noise reduction reduced_noise = nr.reduce_noise(y=data, sr=rate) ...
这里使用noisereduce来进行降噪: pipinstallnoisereduce 编写降噪代码: fromscipy.ioimportwavfileimportnoisereduceasnr# load datarate, data = wavfile.read("./output/test/vocals.wav")# perform noise reductionreduced_noise = nr.reduce_noise(y=data, sr=rate) ...