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| <syntaxhighlight lang="python"> | | <syntaxhighlight lang="python"> |
|
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| import pyaudio
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| #import wave
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| import multiprocessing
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| import numpy as np
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| #import pickle #Not good for np arrays
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| import time
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| from pathlib import Path
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| audio = pyaudio.PyAudio() # create pyaudio instantiation
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| info = audio.get_host_api_info_by_index(0)
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| numdevices = info.get('deviceCount')
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| for i in range(0, numdevices):
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| if (audio.get_device_info_by_host_api_device_index(0, i).get('maxInputChannels')) > 0:
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| print( "Input Device id ", i, " - ", audio.get_device_info_by_host_api_device_index(0, i).get('name') )
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| form_1 = pyaudio.paInt16 # 16-bit resolution
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| chans = 1 # 1 channel
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| samp_rate = 44100 # 44.1kHz sampling rate
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| chunk = 4096 # 2^12 samples for buffer
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| record_secs = 10 # seconds to record
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| dev_index = 2 # device index found by p.get_device_info_by_index(ii)
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| wav_output_filename = 'test1.wav' # name of .wav file
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| print("recording")
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| frames = []
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| </syntaxhighlight> | | </syntaxhighlight> |
Latest revision as of 09:53, 16 February 2021
Introduction
Use USB microphone to listen sound and FFT it to waveforms.
Theory
