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Contributors will listen to audio recordings and compare them against prompt text to identify and correct minor errors. They will also apply specific quality tags to categorize major discrepancies such as noise or mispronunciations.
Our enterprise client, a leading provider of high-quality, diverse datasets for AI model development is seeking skilled native speakers to support a Recording Quality Assurance (RecQA) initiative. In this role, you will listen to existing audio recordings, compare them against the corresponding prompt text, correct minor text-audio mismatches, and identify larger recording or quality issues using defined categories. Your careful review will help ensure high-quality speech data for the client's AI training initiative
Work Assignment and Task Summary (What to Expect)
Contributors will evaluate audio recordings against corresponding prompt text. The role requires carefully listening to each recording to make direct text edits for minor errors (e.g., missing/added words, mispronunciations, or punctuation) and applying specific issue tags (such as Mismatch, Cutoff, Mumble, or Noise) for major discrepancies, ensuring high accuracy and consistent quality across all reviews.
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