Datasets:
Formats:
csv
Size:
< 1K
Tags:
speech-recognition
code-switching
nigerian-languages
asr-benchmark
sahara-codeswitch-challenge
License:
| """ | |
| _common.py — shared plumbing for the transcription scripts. | |
| Every transcribe_*.py does the same three things: | |
| 1. read the list of clips (clip_id + wav path) for a language, | |
| 2. run each clip through one engine, | |
| 3. write results/<engine>.csv in the shared schema: clip_id,engine,transcript | |
| This module holds steps 1 and 3 so each engine script only has to implement | |
| "given a wav path, return a transcript string". That keeps the engines honest: | |
| they all read the exact same audio and write the exact same shape, which is the | |
| whole point of a fair benchmark. | |
| """ | |
| import csv | |
| import os | |
| REPO_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) | |
| AUDIO_DIR = os.path.join(REPO_ROOT, "audio") | |
| RESULTS_DIR = os.path.join(REPO_ROOT, "results") | |
| GROUND_TRUTH_CSV = os.path.join(AUDIO_DIR, "ground_truth.csv") | |
| def load_clips(language): | |
| """ | |
| Return [(clip_id, wav_path), ...] for one language, read from | |
| ground_truth.csv. Verifies each wav actually exists on disk so a missing | |
| file fails loudly here instead of deep inside an engine call. | |
| """ | |
| if not os.path.exists(GROUND_TRUTH_CSV): | |
| raise SystemExit( | |
| f"[STOP] {GROUND_TRUTH_CSV} not found. Run prepare_data.py first " | |
| f"(Step 3) to generate the clips and ground truth." | |
| ) | |
| clips = [] | |
| with open(GROUND_TRUTH_CSV, newline="", encoding="utf-8") as f: | |
| reader = csv.DictReader(f) | |
| for row in reader: | |
| if row.get("language") != language: | |
| continue | |
| clip_id = row["clip_id"] | |
| wav_path = os.path.join(AUDIO_DIR, language, f"{clip_id}.wav") | |
| if not os.path.exists(wav_path): | |
| raise SystemExit( | |
| f"[STOP] Ground truth lists '{clip_id}' but {wav_path} is " | |
| f"missing. Re-run prepare_data.py for '{language}'." | |
| ) | |
| clips.append((clip_id, wav_path)) | |
| if not clips: | |
| raise SystemExit( | |
| f"[STOP] No clips found for language '{language}' in " | |
| f"{GROUND_TRUTH_CSV}. Did prepare_data.py run for this language?" | |
| ) | |
| return clips | |
| def write_results(engine, rows): | |
| """ | |
| Write results/<engine>.csv with the shared schema. `rows` is a list of | |
| (clip_id, transcript) — the engine name is filled in here so it's spelled | |
| identically for the scorer to join on. | |
| """ | |
| os.makedirs(RESULTS_DIR, exist_ok=True) | |
| out_path = os.path.join(RESULTS_DIR, f"{engine}.csv") | |
| with open(out_path, "w", newline="", encoding="utf-8") as f: | |
| writer = csv.writer(f) | |
| writer.writerow(["clip_id", "engine", "transcript"]) | |
| for clip_id, transcript in rows: | |
| writer.writerow([clip_id, engine, transcript]) | |
| print(f"\n[done] Wrote {len(rows)} rows to {out_path}") | |
| return out_path | |
| def require_env(name, how_to_fix): | |
| """Fetch an API key from the environment or stop with a clear message.""" | |
| value = os.environ.get(name) | |
| if not value: | |
| raise SystemExit( | |
| f"[STOP] Environment variable {name} is not set.\n{how_to_fix}" | |
| ) | |
| return value | |