import dataclasses from pathlib import Path import shutil import csv from typing import Any, Optional import srt import soundfile as sf @dataclasses.dataclass class Subtitle: start: float end: float content: str @property def duration(self): return self.end - self.start @classmethod def from_sub(cls, sub: srt.Subtitle): return cls( start=sub.start.total_seconds(), end=sub.end.total_seconds(), content=sub.content ) @classmethod def merge(cls, sub1: 'Subtitle', sub2: 'Subtitle'): return cls( start=sub1.start, end=sub2.end, content=f"{sub1.content.strip()} {sub2.content.strip()}" ) def merge_subs(subs: list[Subtitle], max_sample_duration_s: float) -> list[Subtitle]: merged_subs: list[Subtitle] = [] previous_sub: Subtitle = subs[0] for sub in subs[1:]: # there is a short silence between subs or we reach max duration if previous_sub.end + 0.2 < sub.start or previous_sub.duration + sub.duration > max_sample_duration_s: merged_subs.append(previous_sub) previous_sub = sub elif previous_sub and previous_sub.end + 0.2 >= sub.start: previous_sub = Subtitle.merge(previous_sub, sub) else: raise ValueError("Subtitles are not in order") merged_subs.append(previous_sub) return merged_subs original_audios_path = Path("darija-test-folder") dataset_path = Path("audio_dataset/data/test") max_sample_duration_s = 30 if dataset_path.exists(): shutil.rmtree(dataset_path) dataset_path.mkdir(parents=True) file_to_subs: dict[Path, list[Subtitle]] = {} for file in original_audios_path.iterdir(): if file.suffix == ".wav": with open(file.parent / f"{file.stem}.srt", "r") as f: subs = srt.parse(f.read()) file_to_subs[file] = merge_subs([Subtitle.from_sub(sub) for sub in subs], max_sample_duration_s) columns = ["file_name", "transcription", "sample_id", "start_timestamp", "end_timestamp", "audio_name"] csv_lines: list[dict[str, Any]] = [] for file in file_to_subs: audio, sr = sf.read(file) for sub in file_to_subs[file]: file_name = f"{file.stem}-{sub.start:.2f}-{sub.end:.2f}.wav" audio_cut = audio[int(round(sub.start * sr)): int(round(sub.end * sr))] sf.write(dataset_path / file_name, audio_cut, sr) csv_lines.append({ "file_name": Path("data") / "test" / file_name, "transcription": sub.content, "sample_id": Path(file_name).stem, "start_timestamp": sub.start, "end_timestamp": sub.end, "audio_name": file.stem }) with (dataset_path.parent / "metadata.csv").open('w', encoding="utf-8") as f: writer = csv.DictWriter(f, fieldnames=columns) writer.writeheader() writer.writerows(csv_lines)