What the work involves
You receive audio samples — some clean, some recorded in noisy rooms, over phone lines, or with overlapping speakers — and produce verbatim transcriptions in Mandarin, English, or both when a recording code-switches. Verbatim means what was actually said: fillers, false starts, repetitions, regional pronunciations, and self-corrections stay in unless the guidelines say otherwise. On top of the raw text you apply the project's tagging conventions — speaker labels, inaudible and crosstalk markers, non-speech events, timestamps at specified intervals — and add contextual notes when a passage is genuinely ambiguous rather than silently guessing.
A second part of the job is quality control: reviewing and correcting your own transcripts and, on some batches, passing over work produced by others or by an ASR system. Expect to flag recurring guideline gaps to coordinators instead of resolving them differently on each file. Consistency across a batch matters more to the downstream model than any single elegant judgement call.
What the screen looks for
micro1's screening is AI-led and short. It probes native-level Mandarin listening — including accented and dialect-influenced Putonghua — your handling of Simplified versus Traditional output, character and punctuation conventions, and how you decide between `[inaudible]`, a best guess, and an annotator note. Expect follow-ups that push on specific conventions rather than accepting a general claim of accuracy. Prior AI work is not required; demonstrable transcription discipline is.
Logistics
- Fully remote, contractor engagement, paid hourly against tracked or delivered work
- Largely asynchronous: batches arrive with deadlines, not fixed shift hours
- Volume fluctuates by project phase; treat it as part-time and variable unless told otherwise
- You supply your own computer, reliable internet, and good headphones; a foot pedal or transcription editor helps but is not mandated
