ifile = wave.open("input.wav")
how can I write this file into a numpy float array now?
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@JoranBeasley it has to be float.IAM– IAM2013-05-27 18:51:31 +00:00Commented May 27, 2013 at 18:51
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4 Answers
>>> from scipy.io.wavfile import read
>>> a = read("adios.wav")
>>> numpy.array(a[1],dtype=float)
array([ 128., 128., 128., ..., 128., 128., 128.])
Typically it would be bytes which are then ints... here we just convert it to float type.
You can read about read here: https://docs.scipy.org/doc/scipy/reference/tutorial/io.html#module-scipy.io.wavfile
1 Comment
IAM
thanks! one more question, how could I do this for all .wav-files in the current working directory? I mean saving each file in a cycle in an array, and concentrating it by the end of each step to a main array?
Seven years after the question was asked...
import wave
import numpy
# Read file to get buffer
ifile = wave.open("input.wav")
samples = ifile.getnframes()
audio = ifile.readframes(samples)
# Convert buffer to float32 using NumPy
audio_as_np_int16 = numpy.frombuffer(audio, dtype=numpy.int16)
audio_as_np_float32 = audio_as_np_int16.astype(numpy.float32)
# Normalise float32 array so that values are between -1.0 and +1.0
max_int16 = 2**15
audio_normalised = audio_as_np_float32 / max_int16
9 Comments
Unsigned_Arduino
How should I install the
wave module? pip install wave?
Matthew Walker
@Unsigned_Arduino Have you just tried it? According to the docs, the wave module has been part of Python since at least version 2.7, and it's still included in version 3.8: docs.python.org/3.8/library/wave.html
Unsigned_Arduino
Just tried it, it's included. I never seen this module before so I questioned it's existance in the PSL.
Trees
Hi Matthew Walker, thanks for such a nice answer. I want to ask, that the size of audio_normalised is twice that of samples, so is it representing data for 2 channels, or sth else, please can you elaborate a bit?
Matthew Walker
@avocado getsampwidth() returns the sample width in bytes, so 2 bytes =>
int16, or 4 bytes => int32. I guess I just hadn't come across WAV files with anything other than 2 bytes per sample. Good point. |
Use librosa package and simply load wav file to numpy array with:
y, sr = librosa.load(filename)
loads and decodes the audio as a time series y, represented as a one-dimensional NumPy floating point array. The variable sr contains the sampling rate of y, that is, the number of samples per second of audio. By default, all audio is mixed to mono and resampled to 22050 Hz at load time. This behavior can be overridden by supplying additional arguments to librosa.load().
More information at Librosa library documentation
Comments
Don't have enough reputation to comment underneath @Matthew Walker 's answer, so I make a new answer to add an observation to Matt's answer. max_int16 should be 2**15-1 not 2**15.
Better yet, I think the normalization line should be replaced with:
audio_normalised = audio_as_np_float32 / numpy.iinfo(numpy.int16).max
If the audio is stereo (i.e. two channels) the left right values are interleaved, so to get the stereo array the following can be used :
channels = ifile.getnchannels()
audio_stereo = np.empty((int(len(audio_normalised)/channels), channels))
audio_stereo[:,0] = audio_normalised[range(0,len(audio_normalised),2)]
audio_stereo[:,1] = audio_normalised[range(1,len(audio_normalised),2)]
I believe this answers @Trees question in the comments section.
1 Comment
Matthew Walker
The issue with the definition of
max_int16 is interesting. The range of 16 bit integers is -32,768 to 32,767. If we want to scale from -1 to 1 then we want to divide by the largest possible value, in an absolute sense, or 32,768, which is 2**15. Hence the definition of max_int16 in my answer.