Freelance Transcriptionist - Afrikaans

Posted 22 Days Ago
Be an Early Applicant
2 Locations
Remote
Entry level
Artificial Intelligence • Machine Learning • Robotics • Software
The Role
Transcribe two-speaker Afrikaans audio recordings manually, producing accurate sequential transcripts with speaker labels and HH:MM:SS timestamps. Maintain a word error rate of 5% or less, ensure channel-to-speaker accuracy, meet daily output targets, incorporate feedback, and correct files that fail quality standards. The role requires at least four hours of daily availability, independent work, a computer, and stable internet. Prior transcription experience is beneficial but not required; contributors must pass a qualification test.
Summary Generated by Built In

About Perle

Perle is an AI infrastructure company building expert-driven training data, evaluation systems, and applied AI products for the world's leading labs and enterprises. We specialize in the work that requires real human judgment: domain expertise, linguistic nuance, and cultural fidelity that generic data vendors cannot deliver.


Perle is hiring a freelance transcriptionist fluent in Afrikaans for a remote transcription role. This is a paid contract position open to qualified contributors worldwide.


1. Role Overview

You will transcribe 2-speaker, channel-separated audio recordings in Afrikaans. Each file has two clearly separated speakers. Your job is to produce a clean, accurate, sequentially ordered transcript with speaker labels and timestamps.


2. What You Will Do

  • Listen to 2-speaker audio recordings in Afrikaans
  • Type out what each speaker says, accurately and in full
  • Label each speaker turn as Speaker 1 or Speaker 2, matching the audio channel
  • Add timestamps at the start of each speaker turn (format: HH:MM:SS)
  • Ensure transcripts are sequential with no unexplained gaps


3. Requirements

  • Native or near-native fluency in Afrikaans (spoken and written)
  • Strong written Afrikaans — accurate spelling, punctuation, and grammar
  • Ability to work independently and meet daily output targets
  • Access to a computer with a stable internet connection
  • Availability for at least 4 hours per day
  • Prior transcription experience is a plus but not required — all contributors must pass a qualification test


4. Quality Standard

  • Word Error Rate (WER) of 5% or less on all delivered transcripts
  • Zero speaker label errors — Speaker 1 must always correspond to Channel 1
  • Transcripts reviewed on a rolling basis; feedback provided promptly
  • Files that do not meet the quality threshold will be returned for correction


5. Project Details

Detail

Information

Language required

Afrikaans

Project type

Audio transcription (manual)

Commitment

~at least 4 hours/day (remote, flexible schedule)

Start date

As soon as qualified — rolling onboarding


6. How to Apply

Submit your application through the Perle platform. Applicants who pass the resume check will be onboarded immediately and assigned to production tasks.


Perle is an equal opportunity employer. We welcome applicants from all backgrounds.


Skills Required

  • Native or near-native fluency in spoken and written Afrikaans
  • Strong written Afrikaans, including accurate spelling, punctuation, and grammar
  • Ability to work independently and meet daily output targets
  • Access to a computer with a stable internet connection
  • Availability for at least 4 hours per day
  • Pass the qualification test
  • Prior transcription experience
  • Word Error Rate of 5% or less on delivered transcripts
  • Zero speaker label errors, with Speaker 1 corresponding to Channel 1
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The Company
26 Employees
Year Founded: 2024

What We Do

Perle is an AI infrastructure company that builds expert-driven training data, evaluation systems, and applied AI products for leading labs and enterprises. Based in San Francisco with experts across more than forty markets, it provides human-judgment-intensive domain expertise, linguistic nuance, and cultural fidelity. Its platform supports end-to-end training data, evaluation, labeling, and multimodal data programs for teams developing AI and robotics.

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