defsave_audio(file_path,audio_data,framerate):# 创建一个新的WAV音频文件output_wav=wave.open(file_path,'wb')output_wav.setnchannels(1)# 一声道output_wav.setsampwidth(2)# 16位深度output_wav.setframerate(framerate)# 设置采样率output_wav.writeframes(audio_data.tobytes())# 写入音频数据output...
audio_stream: bytes) -> np.ndarray: pcm = np.frombuffer(audio_stream, dtype=np.float32)if pcm.size == :raise ValueError("音频数据为空") features = np.expand_
data(bytes): numpy.ndarray类型的音频数据 sample_rate(int): 音频样本采样率返回:AudioSegment:音频片段实例 示例代码:import soundfile from yeaudio.audio import AudioSegment samples, sample_rate = soundfile.read('data/test.wav') audio_segment = AudioSegment.from_ndarray(samples, sample_rate=16000) ...
load(test_audio_path) # Return as numpy array instead of bytes 22 24 23 25 @pytest_asyncio.fixture 24 26 async def mock_model_manager(mock_audio_output): 25 27 """Mock model manager for testing.""" 26 28 manager = AsyncMock(spec=ModelManager) 27 29 manager.get_backend = ...
另一块又区分不了是哪块，只能将3块硬盘重新接到备用机上，取消RAID软阵列后，再拿到需要添加RAID软...
pyaudio http://people.csail.mit.edu/hubert/pyaudio/ numpy https://www.runoob.com/numpy/numpy-...
returns the sampling rate (Fs) of the audio file and a NumPy array of the raw audio samples. To get the duration in seconds, one simply needs to divide the number of samples by Fs ShortTermFeatures.feature_extraction() function returns (a) a 68 x 20 short-term feature matrix, where ...
array([feat.shape[2]], dtype=np.int32) chunk_token = ( self.ort_session.run( None, { self.ort_session.get_inputs()[0] .name: feat.detach() .cpu() .numpy(), self.ort_session.get_inputs()[1].name: feat_len, }, )[0] .flatten() .tolist() ) ...
to(device) # SoVits 将预测得到的语义特征(pred_semantic)和音素序列转换为波形数据 audio = ( vq_model.decode( pred_semantic, torch.LongTensor(phones2).to(device).unsqueeze(0), refer ) .detach() .cpu() .numpy()[0, 0] ) ###试试重建不带上prompt部分 max_audio = np....
y = np.array(a.get_array_of_samples()) if a.channels == 2: y = y.reshape((-1, 2)) if normalized: if y.dtype == np.int16: power = 15 elif y.dtype == np.int32: power = 31 else: raise Exception return np.float32(y) / 2**power, a.frame_rate # convert to float32 ...