Add back preprocess_audio for converting audio sample rate. It's

faster to do this once when converting an audio file many times.

preprocess_audio.py

@@ -0,0 +1,42 @@
+"""Converts an input file to 1.024MHz wav file used by encode_audio.py"""
+
+import argparse
+import librosa
+import numpy
+import soundfile
+
+
+def preprocess(
+        filename: str, target_sample_rate: int, normalize: float = 1.0,
+        normalization_percentile: int = 100) -> numpy.ndarray:
+    """Upscale input audio to target sample rate and normalize signal."""
+
+    data, _ = librosa.load(filename, sr=target_sample_rate, mono=True)
+
+    max_value = numpy.percentile(data, normalization_percentile)
+    data /= max_value
+    data *= normalize
+
+    return data
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--clock", choices=['pal', 'ntsc'],
+                        help="Whether target machine clock speed is PAL ("
+                             "1015657Hz) or NTSC (1020484)",
+                        required=True)
+    parser.add_argument("input", type=str, help="input audio file to convert")
+    parser.add_argument("output", type=str, help="output audio file")
+    args = parser.parse_args()
+
+    # Effective clock rate, including every-65 cycle "long cycle" that takes
+    # 16/14 as long.
+    sample_rate = 1015657 if args.clock == 'pal' else 1020484  # NTSC
+
+    soundfile.write(args.output, preprocess(args.input, sample_rate),
+                    sample_rate)
+
+
+if __name__ == "__main__":
+    main()