Datasets:
File size: 2,435 Bytes
ec26866 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 | def curate_dataset(
min_dur,
max_dur,
max_wer,
csv1_path,
csv2_path,
full_dataset_path,
output_path=None,
):
if output_path is None:
wer_str = str(max_wer).replace(".", "")
output_path = (
f"manifest_filtered_{min_dur}_{max_dur}_{wer_str}.csv"
)
# --- Read CSVs ---
df1 = pd.read_csv(csv1_path)
df2 = pd.read_csv(csv2_path)
# --- Ensure numeric types ---
for df in (df1, df2):
df["duration"] = pd.to_numeric(df["duration"], errors="coerce")
df["wer"] = pd.to_numeric(df["wer"], errors="coerce")
# --- Apply filters on each CSV ---
f1 = df1[
(df1["duration"] > min_dur)
& (df1["duration"] < max_dur)
& (df1["wer"] < max_wer)
]
f2 = df2[
(df2["duration"] > min_dur)
& (df2["duration"] < max_dur)
& (df2["wer"] < max_wer)
]
# --- Keep audio_id present in both filtered CSVs ---
ids1 = set(f1["audio_id"].dropna().astype(str))
ids2 = set(f2["audio_id"].dropna().astype(str))
kept_ids = ids1.intersection(ids2)
print(f"Kept audio_id count: {len(kept_ids)}")
# --- Filter the full dataset ---
full_df = pd.read_csv(full_dataset_path)
full_df["audio_id"] = full_df["audio_id"].astype(str)
filtered_full_df = full_df[full_df["audio_id"].isin(kept_ids)]
# --- Save result ---
filtered_full_df.to_csv(output_path, index=False)
print(f"Filtered dataset saved to: {output_path}")
print(f"Rows kept in full dataset: {len(filtered_full_df)}")
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Filter the dataset using duration and WER thresholds."
)
parser.add_argument("--min-dur", type=float, required=True)
parser.add_argument("--max-dur", type=float, required=True)
parser.add_argument("--max-wer", type=float, required=True)
parser.add_argument("--csv1-path", required=True)
parser.add_argument("--csv2-path", required=True)
parser.add_argument("--full-dataset-path", required=True)
parser.add_argument("--output-path", default=None)
args = parser.parse_args()
curate_dataset(
min_dur=args.min_dur,
max_dur=args.max_dur,
max_wer=args.max_wer,
csv1_path=args.csv1_path,
csv2_path=args.csv2_path,
full_dataset_path=args.full_dataset_path,
output_path=args.output_path,
) |