97 lines
2.3 KiB
Python
97 lines
2.3 KiB
Python
import os
|
|
import numpy as np
|
|
import tempfile
|
|
import soundfile as sf
|
|
import torch
|
|
import librosa
|
|
|
|
def load_audio(file_path, target_sr=16000):
|
|
"""
|
|
加载音频文件并转换为指定采样率
|
|
|
|
参数:
|
|
file_path: 音频文件路径
|
|
target_sr: 目标采样率，默认16000Hz
|
|
|
|
返回:
|
|
(numpy array, int): 音频数据和采样率
|
|
"""
|
|
try:
|
|
audio, sr = librosa.load(file_path, sr=target_sr, mono=True)
|
|
return audio, sr
|
|
except Exception as e:
|
|
print(f"加载音频文件失败: {e}")
|
|
return None, None
|
|
|
|
def save_audio(audio_data, sample_rate, file_path):
|
|
"""
|
|
保存音频数据到文件
|
|
|
|
参数:
|
|
audio_data: 音频数据 (numpy array)
|
|
sample_rate: 采样率
|
|
file_path: 保存路径
|
|
|
|
返回:
|
|
bool: 是否保存成功
|
|
"""
|
|
try:
|
|
sf.write(file_path, audio_data, sample_rate)
|
|
return True
|
|
except Exception as e:
|
|
print(f"保存音频文件失败: {e}")
|
|
return False
|
|
|
|
def audio_to_tensor(audio_data, sample_rate=16000):
|
|
"""
|
|
将音频数据转换为张量
|
|
|
|
参数:
|
|
audio_data: 音频数据 (numpy array)
|
|
sample_rate: 采样率
|
|
|
|
返回:
|
|
torch.Tensor: 音频张量
|
|
"""
|
|
# 确保音频是单声道
|
|
if len(audio_data.shape) > 1:
|
|
audio_data = np.mean(audio_data, axis=1)
|
|
|
|
# 转换为torch张量
|
|
audio_tensor = torch.from_numpy(audio_data).float()
|
|
|
|
return audio_tensor, sample_rate
|
|
|
|
def tensor_to_audio(audio_tensor, sample_rate=16000):
|
|
"""
|
|
将音频张量转换为numpy数组
|
|
|
|
参数:
|
|
audio_tensor: 音频张量
|
|
sample_rate: 采样率
|
|
|
|
返回:
|
|
(numpy array, int): 音频数据和采样率
|
|
"""
|
|
if isinstance(audio_tensor, torch.Tensor):
|
|
audio_data = audio_tensor.detach().cpu().numpy()
|
|
else:
|
|
audio_data = audio_tensor
|
|
|
|
return audio_data, sample_rate
|
|
|
|
def get_temp_file(suffix=".wav"):
|
|
"""
|
|
生成临时文件路径
|
|
|
|
参数:
|
|
suffix: 文件后缀
|
|
|
|
返回:
|
|
str: 临时文件路径
|
|
"""
|
|
temp_file = tempfile.NamedTemporaryFile(suffix=suffix, delete=False)
|
|
temp_path = temp_file.name
|
|
temp_file.close()
|
|
return temp_path
|