Joining .wav files without writing on disk in Python

Question

I have a list of .wav files in binary format (they are coming from a websocket), which I want to join in a single binary .wav file to then do speech recognition with it. I have been able to make it work with the following code:

audio = [binary_wav1, binary_wav2,..., binary_wavN] # a list of .wav binary files coming from a socket
audio = [io.BytesIO(x) for x in audio]

# Join wav files
with wave.open('/tmp/input.wav', 'wb') as temp_input:
    params_set = False
    for audio_file in audio:
        with wave.open(audio_file, 'rb') as w:
            if not params_set:
                temp_input.setparams(w.getparams())
                params_set = True
            temp_input.writeframes(w.readframes(w.getnframes()))

# Do speech recognition
binary_audio = open('/tmp/input.wav', 'rb').read())
ASR(binary_audio)

The problem is that I don't want to write the file '/tmp/input.wav' in disk. Is there any way to do it without writing any file in the disk?

Thanks.

Streak

Sound can be represented as 1D array when mono, 2d as stereo. Use something like wavefile to get the raw data. – Ornis

wave.open accepts either a file path or a file like object. you've already imported BytesIO so just use one of those as a file like buffer. Here's and example of someone doing basically just that with gzip (note the slightly different argument names). – Portentous

Answer 1

The general solution for having a file but never putting it to disk is a stream. For this we use the io library which is the default library for working with in-memory streams. You even already use BytesIO earlier in your code it seems.

audio = [binary_wav1, binary_wav2,..., binary_wavN] # a list of .wav binary files coming from a socket
audio = [io.BytesIO(x) for x in audio]

# Join wav files

params_set = False
temp_file = io.BytesIO()
with wave.open(temp_file, 'wb') as temp_input:
    for audio_file in audio:
        with wave.open(audio_file, 'rb') as w:
            if not params_set:
                temp_input.setparams(w.getparams())
                params_set = True
            temp_input.writeframes(w.readframes(w.getnframes()))

#move the cursor back to the beginning of the "file"
temp_file.seek(0)
# Do speech recognition
binary_audio = temp_file.read()
ASR(binary_audio)

note I don't have any .wav files to try this out on. It's up to the wave library to handle the difference between real files and buffered streams properly.

Portentous

Thanks, This works! I had tried it before but i was missing the temp_file.seek(0) statement, so I was just reading an empty binary object then. – Petrology

Answer 2

With scipy and numpy you can read the wav files as numpy arrays and than do the modifications you want.

from scipy.io import wavfile
import numpy as np

# load files
_, arr1 = wavfile.read('song.wav')
_, arr2 = wavfile.read('Aaron_Copland-Quiet_City.wav')

print(arr1.shape)
print(arr2.shape)

>>> (1323001,)
>>> (1323000,)

# make new array by concatenating two audio waves
new_arr = np.hstack((arr1, arr2))
print(new_arr.shape)

>>> (2646001,)

# save new audio wave
wavfile.write('new_audio.wav')

Libratory

This works, but adding a dependency to scipy and/or numpy seems overkill. As @Portentous pointed out in his answer, you can simply write to file-like objects like BytesIO. – Dative