Audiobook QA Expert — English (US)
Mercor (client confidential) · Remote — preferred: United States · Remote
- Pay
- $20–25/hr
- Commitment
- hourly
- Hours / week
- ~20
- Source
- mercor
About this role
**Help make the next generation of AI-narrated audiobooks sound genuinely human.** ## 1. Overview We're building a team of native English speakers who love audiobooks to help evaluate AI-narrated (text-to-speech) audiobooks in US / North American English. You'll listen the way a real audiobook fan does — but with a careful, analytical ear — and flag the moments where the narration slips, so the underlying models can be made better. This is remote, part-time work at roughly 20 hours per week (about 4 hours per day). You can be based anywhere, though we prefer people living in a region where English is natively spoken. ## 2. What You'll Do - Listen to AI-narrated audiobooks in English and assess how natural, accurate, and enjoyable the narration is. - Spot and log errors in the synthesized speech — skipped, added, or mispronounced words; numbers read incorrectly; abbreviations expanded wrongly; unnatural phrasing or intonation; audio glitches and artifacts. - Categorize each issue and mark the exact span where it occurs, using our review tooling. - Report on overall listener satisfaction and where the narration feels natural versus where it breaks the experience. - Work consistently and carefully across many hours of audio without losing attention to detail. ## 3. Who We're Looking For - Native or near-native fluency in English (US / North American English), and an active, genuine audiobook listener — someone who listens regularly and has real opinions about what makes a good listen. - Enough working English to report clearly and communicate with the team. - Some experience with annotation, labeling, transcription, proofreading, linguistics, or other detail-oriented review work. - A sharp, patient ear and the discipline to stay accurate over long listening sessions. - Reliable availability of about 20 hours per week on a part-time basis. ## Nice to Have - Prior experience on AI training-data, model-evaluation, or audio/QA annotation projects. - A background in language, editing, voice, or audio production.
Skills & domains
- ai-training
- rlhf
- sme
- annotation
- Language and Audio