French Audio Transcriptionist (AI Training)

This opportunity is ideal for native French speakers with strong listening skills who are comfortable identifying nuances in spoken audio and working independently on transcription and transcript-cleanup tasks.

• Produce accurate transcriptions of spoken French audio.
• Clean up and correct French audio transcripts.
• Carefully identify details such as crosstalk, filled pauses, background noise, and multiple speakers.
• Follow detailed transcription, style, and formatting guidelines.
• Work independently and asynchronously on your own schedule.
• Maintain accuracy and consistency across assigned transcription tasks.

• Native speaker of French.
• Strong listening skills and attention to detail.
• Comfortable working independently without direct supervision.
• Self-motivated and reliable.
• Able to follow detailed style and formatting guidelines.

• Previous experience as a transcriptionist.
• Experience as a court reporter.
• Background in subtitle or closed-captioning editing.
• Background in linguistics.
• Previous experience working with annotation platforms.

• Fully remote contract opportunity.
• Work independently and asynchronously on your own schedule.
• Compensation ranges from $10–$35 USD per hour.
• Expected workload is 10–39 hours per week, depending on project needs.
• Work volume may fluctuate throughout the duration of the contract.
• Weekly lump-sum payments for work completed during the previous week.
• If selected, you will receive an Upwork contract offer and instructions for onboarding to the client's tasking platform.
• An active contract is required to receive onboarding instructions, evaluation/assessment access, and payment for the project.

An enterprise client is seeking a high volume of detail-oriented French Transcriptionists to help produce accurate transcriptions of spoken French audio and clean up and correct audio transcripts.

The selected consultants will support the company, a leading AI platform that helps organizations build intelligent applications through high-quality human feedback and data labeling.

Originally posted on Himalayas