Your code is working fine. The problem you are facing is due to the admin rights. The audio file has constant 0 data, therefore, you can't listen to sound in the generated wav file. I suppose your microphone device is installed and working properly. If you are not sure about the audio installation status, then as per operating system do these steps:
MAC OS:
System Preferences->Sound->Input and there you can visualize the bars as make some sound. Make sure the selected device type is Built-in.
Windos OS:
Sound settings and test Microphone by click listen to this device, you may later uncheck it because it will loop back your voice to speakers and will create big noises.
Most probably you are using Mac OS. I had the similar issue, because I was using Atom editor to run the python code. Try to run your code from the terminal of Mac OS (or Power Shell if you are using windows), (in case a popup appears for access to microphone on Mac OS, press Ok). Thats it! your code will record fine. As a tester, please run the code below to check if you can visualize the sound, and make sure to run it through Terminal (No editors or IDEs).
import queue
import sys
from matplotlib.animation import FuncAnimation
import matplotlib.pyplot as plt
import numpy as np
import sounddevice as sd
# Lets define audio variables
# We will use the default PC or Laptop mic to input the sound
device = 0 # id of the audio device by default
window = 1000 # window for the data
downsample = 1 # how much samples to drop
channels = [1] # a list of audio channels
interval = 30 # this is update interval in miliseconds for plot
# lets make a queue
q = queue.Queue()
# Please note that this sd.query_devices has an s in the end.
device_info = sd.query_devices(device, 'input')
samplerate = device_info['default_samplerate']
length = int(window*samplerate/(1000*downsample))
# lets print it
print("Sample Rate: ", samplerate)
# Typical sample rate is 44100 so lets see.
# Ok so lets move forward
# Now we require a variable to hold the samples
plotdata = np.zeros((length,len(channels)))
# Lets look at the shape of this plotdata
print("plotdata shape: ", plotdata.shape)
# So its vector of length 44100
# Or we can also say that its a matrix of rows 44100 and cols 1
# next is to make fig and axis of matplotlib plt
fig,ax = plt.subplots(figsize=(8,4))
# lets set the title
ax.set_title("PyShine")
# Make a matplotlib.lines.Line2D plot item of color green
# R,G,B = 0,1,0.29
lines = ax.plot(plotdata,color = (0,1,0.29))
# We will use an audio call back function to put the data in queue
def audio_callback(indata,frames,time,status):
q.put(indata[::downsample,[0]])
# now we will use an another function
# It will take frame of audio samples from the queue and update
# to the lines
def update_plot(frame):
global plotdata
while True:
try:
data = q.get_nowait()
except queue.Empty:
break
shift = len(data)
plotdata = np.roll(plotdata, -shift,axis = 0)
# Elements that roll beyond the last position are
# re-introduced
plotdata[-shift:,:] = data
for column, line in enumerate(lines):
line.set_ydata(plotdata[:,column])
return lines
ax.set_facecolor((0,0,0))
# Lets add the grid
ax.set_yticks([0])
ax.yaxis.grid(True)
""" INPUT FROM MIC """
stream = sd.InputStream( device = device, channels = max(channels), samplerate = samplerate, callback = audio_callback)
""" OUTPUT """
ani = FuncAnimation(fig,update_plot, interval=interval,blit=True)
with stream:
plt.show()
Save this file as voice.py to a folder (let say AUDIO). Then cd to AUDIO folder from the terminal command and then execute it using:
python3 voice.py
or
python voice.py
depending on your python env name.
