Audiobook QA Expert — English (US)

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Pay

$20-25/hr

Location

Remote — preferred: United States

Difficulty

Medium

Posted

Required Skills

Language and Audio Data Analysis Audio/Voice

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.