Automated quality assurance pipeline for the Voice Scale crowdsourced vegetable-name dataset (English, Tamil, Sinhala). Runs 14 checks across four layers before any clip is accepted into the final dataset.
Raw WAV clips
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Layer 1 — Signal Checks T-01 duration & silence
(runs on every submission) T-02 clipping & distortion
T-03 SNR
T-04 sample rate & format
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Layer 2 — Transcription T-05 Whisper (English)
(catches wrong words) T-06 Whisper (Tamil)
T-07 language ID
T-08 duplicate detection
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Layer 3 — Embedding Analysis T-09 wav2vec2 extractor ← must run first
(catches semantic outliers) T-10 per-class outlier detector
T-11 cross-language consistency
T-12 UMAP visualisation
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Layer 4 — Reporting T-13 aggregator & HTML dashboard
T-14 speaker-level fairness audit
Every task in layers 1–3 writes a CSV with columns clip_id, verdict, reason, score. T-13 merges them all.
| Task | Title | Owner |
|---|---|---|
| T-01 | Duration & silence validator | Praveen |
| T-02 | Clipping & distortion detector | Ashini |
| T-03 | SNR estimator | Chanupa |
| T-04 | Sample rate & format validator | Didula |
| T-05 | Whisper transcription runner (English) | Sheron |
| T-06 | Whisper transcription runner (Tamil) | Thila |
| T-07 | Language ID verifier | Kusal |
| T-08 | Duplicate & near-duplicate detector | Lasana |
| T-09 | wav2vec2 embedding extractor | Sahe |
| T-10 | Per-class outlier detector | Teshan |
| T-11 | Cross-language consistency checker | Yohan |
| T-12 | UMAP visualisation generator | Ifaz |
| T-13 | QA results aggregator & dashboard | Thisen |
| T-14 | Speaker-level fairness auditor | Thisen |
- T-09 must complete before T-10, T-11, T-12 (they all read its
.npyoutput) - T-13 and T-14 must run after all layer 1–3 tasks are complete