Here's my code:
这是我的代码:
from scipy.io import wavfile
fName = 'file.wav'
fs, signal = wavfile.read(fName)
signal = signal / max(abs(signal)) # scale signal
assert min(signal) >= -1 and max(signal) <= 1
And the error is:
错误是:
Traceback (most recent call last):
File = "vad.py", line 10, in <module>
signal = signal / max(abs(signal))
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any()
Can anyone please help me solving this error..?
任何人都可以帮我解决这个错误..?
Thanks in advance..
提前致谢..
1 个解决方案
#1
The line that produces the error shouldn't give an error if your signal were 1D (ie, a mono audio file), so you probably have a stereo wav file and your signal has the shape (nsamples, 2)
. Here's a short example for a stereo signal:
如果您的信号是1D(即单声道音频文件),产生错误的行不应该出错,因此您可能有一个立体声wav文件,并且您的信号具有形状(nsamples,2)。以下是立体声信号的简短示例:
In [109]: x = (np.arange(10, dtype=float)-5).reshape(5,2)
In [110]: x
Out[110]:
array([[-5., -4.],
[-3., -2.],
[-1., 0.],
[ 1., 2.],
[ 3., 4.]])
In [111]: x /= abs(x).max(axis=0) # normalize each channel independently
In [112]: x
Out[112]:
array([[-1. , -1. ],
[-0.6, -0.5],
[-0.2, 0. ],
[ 0.2, 0.5],
[ 0.6, 1. ]])
Your next line will also give you trouble with a 2D array, so there try:
您的下一行也会给您带来2D阵列的麻烦,所以尝试:
(x>=-1).all() and (x<=1).all()
#1
The line that produces the error shouldn't give an error if your signal were 1D (ie, a mono audio file), so you probably have a stereo wav file and your signal has the shape (nsamples, 2)
. Here's a short example for a stereo signal:
如果您的信号是1D(即单声道音频文件),产生错误的行不应该出错,因此您可能有一个立体声wav文件,并且您的信号具有形状(nsamples,2)。以下是立体声信号的简短示例:
In [109]: x = (np.arange(10, dtype=float)-5).reshape(5,2)
In [110]: x
Out[110]:
array([[-5., -4.],
[-3., -2.],
[-1., 0.],
[ 1., 2.],
[ 3., 4.]])
In [111]: x /= abs(x).max(axis=0) # normalize each channel independently
In [112]: x
Out[112]:
array([[-1. , -1. ],
[-0.6, -0.5],
[-0.2, 0. ],
[ 0.2, 0.5],
[ 0.6, 1. ]])
Your next line will also give you trouble with a 2D array, so there try:
您的下一行也会给您带来2D阵列的麻烦,所以尝试:
(x>=-1).all() and (x<=1).all()