import pyaudio

import numpy as np

# Define constants for audio processing

CHUNK_SIZE = 1024

SAMPLE_RATE = 44100

# Define frequency ranges for each note in the musical scale

NOTE_FREQS = {

    'C4': 261.63,

    'D4': 293.66,

    'E4': 329.63,

    'F4': 349.23,

    'G4': 392.00,

    'A4': 440.00,

    'B4': 493.88

}

# Initialize PyAudio stream

audio = pyaudio.PyAudio()

stream = audio.open(format=pyaudio.paInt16, channels=1, rate=SAMPLE_RATE,

                    input=True, frames_per_buffer=CHUNK_SIZE)

print("Listening for audio...")

while True:

    # Read audio data from stream

    data = np.frombuffer(stream.read(CHUNK_SIZE), dtype=np.int16)

    # Apply window function to audio data to improve frequency resolution

    window = np.hamming(len(data))

    data = data * window

    # Perform FFT to extract frequency components

    fft = np.fft.fft(data)

    freqs = np.fft.fftfreq(len(data), 1.0/SAMPLE_RATE)

    freqs = freqs[:len(data)//2]

    fft = np.abs(fft[:len(data)//2])

    # Find peak frequency component

    peak_idx = np.argmax(fft)

    peak_freq = freqs[peak_idx]

    # Match peak frequency to note in musical scale

    note = None

    for n, f in NOTE_FREQS.items():

        if abs(peak_freq - f) < 10:

            note = n

            break

    # Print note if detected

    if note:

        print("Detected note: {}".format(note))

QA: John Nugent, Anthony Mendo, Jackie Fang

Back-end Developers: Gabriel Garcia, Winston Lei, Roshan Soni