import os import re import json import shutil import argparse import librosa import soundfile as sf from tqdm import tqdm # ARGS CONFIGURATION def parse_args(): parser = argparse.ArgumentParser(description="Reproduce mixed Code-Switching Dataset.") parser.add_argument("--secomicsc_root", type=str, required=True, help="Path to 'ASR-SECoMiCSC' folder (must contain TXT and WAV subfolders).") parser.add_argument("--dev_root", type=str, required=True, help="Path to 'ASR-DevCECoMiCSC' folder (must contain TXT and WAV subfolders).") parser.add_argument("--cs_dialogue_root", type=str, required=True, help="Path to CS-Dialogue 'short_wav' folder (must contain SCRIPT and WAVE).") parser.add_argument("--output_dir", type=str, default="./CS_chunks_Dataset", help="Directory to save processed audio and metadata.") return parser.parse_args() # CONSTANTS TARGET_SR = 16000 MIN_DURATION = 5.0 MAX_DURATION = 15.0 MAX_GAP = 1.8 NOISE_TAGS = ["[ENS]", "[NPS]", "[SONANT]", "[*]", "[LAUGHTER]"] # LEGACY PROCESSING LOGIC def parse_legacy_line(line): line = line.strip() if not line: return None m = re.match(r"\[([\d.]+),([\d.]+)\]\s+(.*)", line) if not m: return None start, end = float(m.group(1)), float(m.group(2)) rest = m.group(3).split() if len(rest) < 2: return None text = " ".join(rest[2:]) if len(rest) >= 3 else rest[-1] is_noise = any(tag in text for tag in NOISE_TAGS) return {"start": start, "end": end, "text": text, "is_noise": is_noise} def process_legacy(dataset_name, specific_root_path, meta_f, audio_out_root): print(f"Processing Legacy: {dataset_name}...") txt_dir = os.path.join(specific_root_path, "TXT") wav_dir = os.path.join(specific_root_path, "WAV") # audio/SECoMiCSC sub_dir = os.path.join(audio_out_root, dataset_name) os.makedirs(sub_dir, exist_ok=True) if not os.path.exists(txt_dir): print(f"Skipping {dataset_name}: 'TXT' folder not found inside {specific_root_path}") return files = [f for f in os.listdir(txt_dir) if f.endswith(".txt")] for txt_file in tqdm(files, desc=dataset_name): wav_file = txt_file.replace(".txt", ".wav") wav_path = os.path.join(wav_dir, wav_file) txt_path = os.path.join(txt_dir, txt_file) if not os.path.exists(wav_path): continue try: audio, sr = librosa.load(wav_path, sr=TARGET_SR, mono=True) except: continue with open(txt_path, encoding="utf-8") as f: segments = [parse_legacy_line(l) for l in f if parse_legacy_line(l)] segments.sort(key=lambda x: x["start"]) buffer = [] buffer_start = None last_end = None def flush(): nonlocal buffer, buffer_start if not buffer: return start_t = buffer_start end_t = buffer[-1]["end"] if int(start_t * sr) >= len(audio) or int(end_t * sr) > len(audio): return chunk = audio[int(start_t * sr): int(end_t * sr)] dur = len(chunk) / sr if dur < 0.5 or dur > MAX_DURATION: return texts = [s["text"] for s in buffer if not s["is_noise"]] if not texts: return # Save Chunk fname = f"{dataset_name}_{os.path.basename(wav_path)[:-4]}_{int(start_t*100)}_{int(end_t*100)}.wav" out_path = os.path.join(sub_dir, fname) sf.write(out_path, chunk, sr) # Write Metadata meta_f.write(json.dumps({ "file_name": f"audio/{dataset_name}/{fname}", "sentence": " ".join(texts), "duration": round(dur, 2), "source": dataset_name }, ensure_ascii=False) + "\n") for seg in segments: if not buffer: if seg["is_noise"]: continue buffer, buffer_start = [seg], seg["start"] last_end = seg["end"] continue gap = seg["start"] - last_end est_dur = seg["end"] - buffer_start if gap > MAX_GAP or est_dur > MAX_DURATION: flush() buffer = [] if seg["is_noise"] else [seg] buffer_start = seg["start"] if buffer else None else: buffer.append(seg) last_end = seg["end"] flush() # CS-DIALOGUE PROCESSING LOGIC def process_cs_dialogue(source_root, meta_f, audio_out_root): DATASET_NAME = "CS_Dialogue" script_dir = os.path.join(source_root, "SCRIPT") wave_root = os.path.join(source_root, "WAVE", "C0") sub_dir = os.path.join(audio_out_root, DATASET_NAME) os.makedirs(sub_dir, exist_ok=True) if not os.path.exists(script_dir): print(f"CS-Dialogue SCRIPT dir not found: {script_dir}") return txt_files = [f for f in os.listdir(script_dir) if f.endswith(".txt")] for txt_file in tqdm(txt_files, desc=DATASET_NAME): txt_path = os.path.join(script_dir, txt_file) session_id = os.path.splitext(txt_file)[0] src_audio_folder = os.path.join(wave_root, session_id) if not os.path.exists(src_audio_folder): continue with open(txt_path, 'r', encoding='utf-8') as f: for line in f: line = line.strip() if not line: continue parts = line.split(maxsplit=2) if len(parts) < 3: continue fname_raw, tag, text = parts[0], parts[1], parts[2] if tag != "": continue if not fname_raw.endswith(".wav"): fname_raw += ".wav" src_wav = os.path.join(src_audio_folder, fname_raw) if os.path.exists(src_wav): dst_wav = os.path.join(sub_dir, fname_raw) shutil.copy2(src_wav, dst_wav) try: dur = librosa.get_duration(path=dst_wav) except: dur = 0.0 meta_f.write(json.dumps({ "file_name": f"audio/{DATASET_NAME}/{fname_raw}", "sentence": text, "duration": round(dur, 2), "source": DATASET_NAME, "original_tag": tag }, ensure_ascii=False) + "\n") # MAIN ENTRY if __name__ == "__main__": args = parse_args() audio_out = os.path.join(args.output_dir, "audio") meta_path = os.path.join(args.output_dir, "metadata.jsonl") os.makedirs(audio_out, exist_ok=True) with open(meta_path, 'w', encoding='utf-8') as mf: process_legacy("SECoMiCSC", args.secomicsc_root, mf, audio_out) process_legacy("DevCECoMiCSC", args.dev_root, mf, audio_out) process_cs_dialogue(args.cs_dialogue_root, mf, audio_out) print(f"\nAll Done! Dataset ready at: {args.output_dir}")