This is a modified CircuitPlayground demo, original is here: https://learn.adafruit.com/adafruit-circuit-playground-express/playground-sound-meter. The main modification is to only "detect" when the current magnitude of the mic is above a running average value by some multiplier > 1 (here we used 2.0).

code.py

# The MIT License (MIT)
#
# Copyright (c) 2017 Dan Halbert for Adafruit Industries
# Copyright (c) 2017 Kattni Rembor, Tony DiCola for Adafruit Industries
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.

import array
import audiobusio
import board
import math
import neopixel

# Exponential scaling factor.
# Should probably be in range -10 .. 10 to be reasonable.
CURVE = 2
SCALE_EXPONENT = math.pow(10, CURVE*-0.1)

PEAK_COLOR = (100, 0, 255)
NUM_PIXELS = 10

# Number of samples to read at once.
NUM_SAMPLES = 160

# Restrict value to be between floor and ceiling.
def constrain(value, floor, ceiling):
    return max(floor, min(value, ceiling))

# Scale input_value to be between output_min and output_max, in an exponential way.
def log_scale(input_value, input_min, input_max, output_min, output_max):
    normalized_input_value = (input_value - input_min) / (input_max - input_min)
    return output_min + math.pow(normalized_input_value, SCALE_EXPONENT) * (output_max - output_min)

# Remove DC bias before computing RMS.
def normalized_rms(values):
    minbuf = int(mean(values))
    return math.sqrt(sum(float((sample-minbuf)*(sample-minbuf)) for sample in values)/len(values))

def mean(values):
    return (sum(values) / len(values))

def volume_color(i):
    return (200, i*(255//NUM_PIXELS), 0)

# Main program

# Set up NeoPixels and turn them all off.
pixels = neopixel.NeoPixel(board.NEOPIXEL, NUM_PIXELS, brightness=0.1, auto_write=False)
pixels.fill(0)
pixels.show()

mic = audiobusio.PDMIn(board.MICROPHONE_CLOCK, board.MICROPHONE_DATA, frequency=16000, bit_depth=16)
# Record an initial sample to calibrate. Assume it's quiet when we start.
samples = array.array('H', [0] * NUM_SAMPLES)
mic.record(samples, len(samples))
# Set lowest level to expect, plus a little.
input_floor = normalized_rms(samples) + 10
# OR: used a fixed floor
# input_floor = 50

# You might want to print the input_floor to help adjust other values.
# print(input_floor)

# Corresponds to sensitivity: lower means more pixels light up with lower sound
# Adjust this as you see fit.
input_ceiling = input_floor + 500

peak = 0
N = 5
avg = 0.0


while True:
    mic.record(samples, len(samples))
    magnitude = normalized_rms(samples)
    avg -= avg / N;
    avg += magnitude / N;
    # You might want to print this to see the values.
    print(magnitude, avg)
    
    pixels.fill(0)
    if magnitude/avg >= 2.0 or peak > 0:
        # Compute scaled logarithmic reading in the range 0 to NUM_PIXELS
        c = log_scale(constrain(magnitude, input_floor, input_ceiling), input_floor, input_ceiling, 0, NUM_PIXELS)

        # Light up pixels that are below the scaled and interpolated magnitude.
        
        for i in range(NUM_PIXELS):
            if i < c:
                pixels[i] = volume_color(i)
            # Light up the peak pixel and animate it slowly dropping.
            if c >= peak:
                peak = min(c, NUM_PIXELS-1)
            elif peak > 0:
                peak = peak - 1
            if peak > 0:
                pixels[int(peak)] = PEAK_COLOR
    pixels.show()