delete unrelated file

vad_filter.py

@@ -1,92 +0,0 @@
-import argparse
-import os
-import shutil
-import sys
-from pathlib import Path
-
-import pandas as pd
-import torch
-from tqdm import tqdm
-
-from style_bert_vits2.logging import logger
-
-
-vad_model, utils = torch.hub.load(
-    repo_or_dir="litagin02/silero-vad",
-    model="silero_vad",
-    onnx=True,
-    trust_repo=True,
-)
-
-(get_speech_timestamps, _, read_audio, *_) = utils
-
-
-def get_speech_ratio(audio_file):
-    sampling_rate = 16000
-
-    wav = read_audio(audio_file, sampling_rate=sampling_rate)
-    speech_timestamps = get_speech_timestamps(
-        wav, vad_model, sampling_rate=sampling_rate
-    )
-
-    speech_dur_ms = 0
-
-    for ts in speech_timestamps:
-        start_ms = ts["start"] / 16
-        end_ms = ts["end"] / 16
-        speech_dur_ms += end_ms - start_ms
-
-    total_dur_ms = len(wav) / sampling_rate * 1000
-    return speech_dur_ms / total_dur_ms
-
-
-def process(file: Path):
-    speech_ratio = get_speech_ratio(file)
-    return file, speech_ratio
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Calculate speech ratio.")
-    parser.add_argument(
-        "-i", "--input", help="Directory containing audio files", required=True
-    )
-    args = parser.parse_args()
-
-    if os.path.exists(os.path.join(args.input, "low_speech_ratio")):
-        logger.info("Low speech ratio directory already exists, skipping...")
-        exit(0)
-
-    data_dir = Path(args.input)
-    wav_files = list(data_dir.glob("*.wav"))
-    wav_files.sort()
-
-    if len(wav_files) < 100:
-        logger.warning("Too few files, skipping...")
-        exit(0)
-
-    logger.info(f"Start VAD filtering for {data_dir}...")
-
-    results = []
-
-    for wav_file in tqdm(wav_files, file=sys.stdout):
-        speech_ratio = get_speech_ratio(wav_file)
-        results.append((wav_file, speech_ratio))
-
-    results_df = pd.DataFrame(results, columns=["file", "speech_ratio"])
-    results_df.to_csv(os.path.join(data_dir, "speech_ratio.csv"), index=False)
-
-    logger.info(f"Speech ratio stats:\n{results_df['speech_ratio'].describe()}")
-    threshold = 0.5
-
-    low_speech_ratio_dir = os.path.join(data_dir, "low_speech_ratio")
-    os.makedirs(low_speech_ratio_dir, exist_ok=True)
-
-    low_speech_files = results_df[results_df["speech_ratio"] < threshold]["file"]
-    logger.info(f"Moving {len(low_speech_files)} files to {low_speech_ratio_dir}...")
-    for low_speech_file in low_speech_files:
-        shutil.move(low_speech_file, low_speech_ratio_dir)
-    logger.success("VAD filtering completed.")
-
-
-if __name__ == "__main__":
-    main()