Add back preprocess_audio for converting audio sample rate. It's
faster to do this once when converting an audio file many times.
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"""Converts an input file to 1.024MHz wav file used by encode_audio.py"""
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import argparse
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import librosa
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import numpy
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import soundfile
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def preprocess(
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filename: str, target_sample_rate: int, normalize: float = 1.0,
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normalization_percentile: int = 100) -> numpy.ndarray:
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"""Upscale input audio to target sample rate and normalize signal."""
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data, _ = librosa.load(filename, sr=target_sample_rate, mono=True)
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max_value = numpy.percentile(data, normalization_percentile)
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data /= max_value
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data *= normalize
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return data
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument("--clock", choices=['pal', 'ntsc'],
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help="Whether target machine clock speed is PAL ("
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"1015657Hz) or NTSC (1020484)",
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required=True)
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parser.add_argument("input", type=str, help="input audio file to convert")
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parser.add_argument("output", type=str, help="output audio file")
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args = parser.parse_args()
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# Effective clock rate, including every-65 cycle "long cycle" that takes
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# 16/14 as long.
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sample_rate = 1015657 if args.clock == 'pal' else 1020484 # NTSC
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soundfile.write(args.output, preprocess(args.input, sample_rate),
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sample_rate)
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if __name__ == "__main__":
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main()
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