Noise reduction using pyaudio documentation code

noise.py

"""
Measure the frequencies coming in through the microphone
Patchwork of wire_full.py from pyaudio tests and spectrum.py from Chaco examples
"""

import pyaudio
import numpy as np
import scipy.signal

CHUNK = 1024 * 2

WIDTH = 2
DTYPE = np.int16
MAX_INT = 32768.0

CHANNELS = 1
RATE = 11025 * 1
RECORD_SECONDS = 20

j = np.complex(0, 1)

p = pyaudio.PyAudio()
stream = p.open(format=p.get_format_from_width(WIDTH),
                channels=CHANNELS,
                rate=RATE,
                input=True,
                output=True,
                frames_per_buffer=CHUNK)

print("Recording Audio...")

# initialize filter variables
fir = np.zeros(CHUNK * 2)
fir[:(2 * CHUNK)] = 1.
fir /= fir.sum()

fir_last = fir
avg_freq_buffer = np.zeros(CHUNK)
obj = -np.inf
t = 10

# initialize sample buffer
buffer = np.zeros(CHUNK * 2)

try:
    while True:
        # read audio
        string_audio_data = stream.read(CHUNK)
        audio_data = np.fromstring(string_audio_data, dtype=DTYPE)
        normalized_data = audio_data / MAX_INT
        freq_data = np.fft.fft(normalized_data)

        # synthesize audio
        buffer[CHUNK:] = np.random.randn(CHUNK)
        freq_buffer = np.fft.fft(buffer)
        freq_fir = np.fft.fft(fir)
        freq_synth = freq_fir * freq_buffer
        synth = np.real(np.fft.ifft(freq_synth))

        # adjust fir
        # objective is to make abs(freq_synth) as much like long-term average of freq_buffer
        MEMORY = 100
        avg_freq_buffer = (avg_freq_buffer * MEMORY + np.abs(freq_data)) / (MEMORY + 1)
        obj_last = obj

        obj = np.real(np.dot(avg_freq_buffer[1:51], np.abs(freq_synth[1:100:2])) / np.dot(freq_synth[1:100:2],
                                                                                          np.conj(freq_synth[1:100:2])))
        if obj > obj_last:
            fir_last = fir
        fir = fir_last.copy()

        # adjust filter in frequency space
        freq_fir = np.fft.fft(fir)
        # t += np.clip(np.random.randint(3)-1, 0, 64)
        t = np.random.randint(100)

        freq_fir[t] += np.random.randn() * .05

        # transform frequency space filter to time space, click-free
        fir = np.real(np.fft.ifft(freq_fir))
        fir[:CHUNK] *= np.linspace(1., 0., CHUNK) ** .1
        fir[CHUNK:] = 0

        # move chunk to start of buffer
        buffer[:CHUNK] = buffer[CHUNK:]

        # write audio
        audio_data = np.array(np.round_(synth[CHUNK:] * MAX_INT), dtype=DTYPE)
        string_audio_data = audio_data.tostring()
        stream.write(string_audio_data, CHUNK)
finally:
    stream.stop_stream()
    stream.close()
    p.terminate()

import pyaudio
import numpy as np
import scipy.signal
import wave

CHUNK = 1024

FORMAT = pyaudio.paInt16

WIDTH = 2
DTYPE = np.int16
MAX_INT = 32768.0

CHANNELS = 1
RATE = 16000
RECORD_SECONDS = 7

WAVE_OUTPUT_FILENAME = "Speech.wav"

j = np.complex(0,1)


p = pyaudio.PyAudio()
stream = p.open(format=p.get_format_from_width(WIDTH),
                channels=CHANNELS,
                rate=RATE,
                input=True,
                output=True,
                frames_per_buffer=CHUNK)

print("* recording")

# initialize filter variables
fir = np.zeros(CHUNK * 2)
fir[:(2*CHUNK)] = 1.
fir /= fir.sum()

fir_last = fir
avg_freq_buffer = np.zeros(CHUNK)
obj = -np.inf
t = 10

# initialize sample buffer
buffer = np.zeros(CHUNK * 2)

#for i in np.arange(RATE / CHUNK * RECORD_SECONDS):
while True:
    # read audio
    frames = []
    string_audio_data = stream.read(CHUNK)
    audio_data = np.fromstring(string_audio_data, dtype=DTYPE)
    normalized_data = audio_data / MAX_INT
    freq_data = np.fft.fft(normalized_data)

    # synthesize audio
    buffer[CHUNK:] = np.random.randn(CHUNK)
    freq_buffer = np.fft.fft(buffer)
    freq_fir = np.fft.fft(fir)
    freq_synth = freq_fir * freq_buffer
    synth = np.real(np.fft.ifft(freq_synth))

    # adjust fir
    # objective is to make abs(freq_synth) as much like long-term average of freq_buffer
    MEMORY=100
    avg_freq_buffer = (avg_freq_buffer*MEMORY + \
                           np.abs(freq_data)) / (MEMORY+1)
    obj_last = obj

    obj = np.real(np.dot(avg_freq_buffer[1:51], np.abs(freq_synth[1:100:2])) / np.dot(freq_synth[1:100:2], np.conj(freq_synth[1:100:2])))
    if obj > obj_last:
        fir_last = fir
    fir = fir_last.copy()

    # adjust filter in frequency space
    freq_fir = np.fft.fft(fir)
    #t += np.clip(np.random.randint(3)-1, 0, 64)
    t = np.random.randint(100)
    
    freq_fir[t] += np.random.randn()*.05

    # transform frequency space filter to time space, click-free
    fir = np.real(np.fft.ifft(freq_fir))
    fir[:CHUNK] *= np.linspace(1., 0., CHUNK)**.1
    fir[CHUNK:] = 0


    # move chunk to start of buffer
    buffer[:CHUNK] = buffer[CHUNK:]
    
    # write audio
    audio_data = np.array(np.round_(synth[CHUNK:] * MAX_INT), dtype=DTYPE)
    string_audio_data = audio_data.tostring()
    frames.append(string_audio_data)
    stream.write(string_audio_data, CHUNK)

print("* done")

stream.stop_stream()
stream.close()

p.terminate()

waveFile = wave.open(WAVE_OUTPUT_FILENAME, 'wb')
waveFile.setnchannels(CHANNELS)
waveFile.setsampwidth(p.get_sample_size(FORMAT))
waveFile.setframerate(RATE)
waveFile.writeframes(b''.join(frames))
waveFile.close()

^Above are the changes I made in your code for my use.
If not this, Can you help me with noise reduction through python on wav file, I have to use it for speech recognition, and due to background noise, accuracy of my speech recognition takes a dive.
Anyways, Following is the error I get when I try to run the above code:

runfile('C:/Users/hs45858/NoiseReduction.py', wdir='C:/Users/hs45858')
* recording
C:/Users/hs45858/NoiseReduction.py:58: DeprecationWarning: The binary mode of fromstring is deprecated, as it behaves surprisingly on unicode inputs. Use frombuffer instead
  audio_data = np.fromstring(string_audio_data, dtype=DTYPE)
C:/Users/hs45858/NoiseReduction.py:76: RuntimeWarning: invalid value encountered in true_divide
  obj = np.real(np.dot(avg_freq_buffer[1:51], np.abs(freq_synth[1:100:2])) / np.dot(freq_synth[1:100:2], np.conj(freq_synth[1:100:2])))
Traceback (most recent call last):

  File "<ipython-input-5-4d0a5b75ddd0>", line 1, in <module>
    runfile('C:/Users/hs45858/NoiseReduction.py', wdir='C:/Users/hs45858')

  File "C:\Program Files\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 705, in runfile
    execfile(filename, namespace)

  File "C:\Program Files\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/hs45858/NoiseReduction.py", line 101, in <module>
    stream.write(string_audio_data, CHUNK)

  File "C:\Users\hs45858\AppData\Local\conda\conda\envs\harsh\Lib\site-packages\pyaudio.py", line 586, in write
    exception_on_underflow)

KeyboardInterrupt

Your code is trying to divide by 0. Add this (numpy as np) :
np.seterr(divide='ignore', invalid='ignore')