Add speaking rate script

src/python/piper_train/get_speaking_rate.py

@@ -0,0 +1,72 @@
+#!/usr/bin/env python3
+import argparse
+import csv
+import json
+import sys
+import statistics
+from pathlib import Path
+
+import librosa
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--dataset_dir", default=Path.cwd())
+    parser.add_argument("--csv", action="store_true")
+    args = parser.parse_args()
+
+    dataset_dir = Path(args.dataset_dir)
+    wav_dir = dataset_dir / "wav"
+    if not wav_dir.is_dir():
+        wav_dir = dataset_dir / "wavs"
+
+    reader = csv.reader(sys.stdin, delimiter="|")
+    writer = csv.writer(sys.stdout, delimiter="|")
+    rates = []
+    for row in reader:
+        filename, text = row[0], row[-1]
+
+        # Try file name relative to metadata
+        wav_path = dataset_dir / filename
+
+        if not wav_path.exists():
+            # Try with .wav
+            wav_path = dataset_dir / f"{filename}.wav"
+
+        if not wav_path.exists():
+            # Try wav/ or wavs/
+            wav_path = wav_dir / filename
+
+        if not wav_path.exists():
+            # Try with .wav
+            wav_path = wav_dir / f"{filename}.wav"
+
+        if not wav_path.exists():
+            print("Missing", wav_path, file=sys.stderr)
+            continue
+
+        if wav_path.stat().st_size == 0:
+            print("Empty", wav_path, file=sys.stderr)
+            continue
+
+        duration = librosa.get_duration(path=wav_path)
+        rate = duration / len(text)
+
+        if args.csv:
+            writer.writerow((filename, text, duration, rate))
+        else:
+            rates.append(rate)
+
+    if not args.csv:
+        json.dump(
+            {
+                "rates": rates,
+                "mean": statistics.mean(rates),
+                "median": statistics.median(rates),
+            },
+            sys.stdout,
+        )
+
+
+if __name__ == "__main__":
+    main()