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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def find_speech_regions(filename, frame_width=4096, min_region_size=0.5, max_region_size=6):
 # pylint: disable=too-many-locals """ Perform voice activity detection on a given audio file. """

    reader = wave.open(filename)
    sample_width = reader.getsampwidth()
    rate = reader.getframerate()
    n_channels = reader.getnchannels()
    chunk_duration = float(frame_width) / rate

    n_chunks = int(math.ceil(reader.getnframes()*1.0 / frame_width))
    energies = []

    for _ in range(n_chunks):
        chunk = reader.readframes(frame_width)
        energies.append(audioop.rms(chunk, sample_width * n_channels))

    threshold = percentile(energies, 0.2)

    elapsed_time = 0

    regions = []
    region_start = None

    for energy in energies:
        is_silence = energy <= threshold
        max_exceeded = region_start and elapsed_time - region_start >= max_region_size

        if (max_exceeded or is_silence) and region_start:
            if elapsed_time - region_start >= min_region_size:
                regions.append((region_start, elapsed_time))
                region_start = None

        elif (not region_start) and (not is_silence):
            region_start = elapsed_time
        elapsed_time += chunk_duration
    return regions