We are sharing a specialised remote consulting opportunity for Cantonese language professionals with strong transcription, annotation, and linguistic quality-review skills to contribute to an advanced AI training project focused on high-quality Cantonese and English audio data.
Selected professionals will transcribe and annotate audio recordings, review automatic transcriptions, identify linguistic nuances and speaker variations, and produce clean, time-stamped transcripts that meet defined quality standards. The work requires native-level Cantonese proficiency, excellent attention to detail, and strong sensitivity to dialect, context, and spoken-language variation. No prior experience in AI is required.
Key Responsibilities
Cantonese & English Audio Transcription
Transcribe Cantonese and English audio recordings with a high degree of accuracy and consistency
Capture spoken content faithfully while preserving relevant context and speaker intent
Handle regional accents, dialectal variation, and natural speech patterns carefully
Produce clean, structured transcripts that accurately reflect the underlying audio
Maintain consistency across repeated transcription assignments
Annotation & Automatic Transcript Review
Review and refine automatically generated transcriptions
Correct errors involving wording, punctuation, segmentation, or interpretation
Annotate audio and transcript content according to project-specific linguistic guidelines
Identify language nuances, contextual cues, and ambiguous passages requiring further review
Apply transcription and annotation standards consistently across assignments
Timestamping & Quality Assurance
Deliver time-stamped transcripts according to defined formatting requirements
Proofread and validate completed work for accuracy, completeness, and consistency
Identify and correct transcription or annotation errors before submission
Ensure deliverables meet established quality benchmarks
Maintain strong attention to detail throughout the transcription and review process
Linguistic Collaboration & Project Delivery
Collaborate with project leads to resolve unclear or ambiguous audio content
Communicate linguistic edge cases and transcription challenges clearly
Contribute Cantonese-language insights that improve the quality of AI training data
Incorporate reviewer feedback and evolving project guidelines into future work
Submit deliverables according to established project timelines and milestones
Ideal Profile
Native proficiency in Cantonese
Strong understanding of regional Cantonese dialectal variation
Demonstrated professional experience in audio transcription
Experience working with both Cantonese and English audio content is strongly preferred
Exceptional attention to detail, accuracy, and linguistic sensitivity
Proficiency with transcription tools and audio playback software
Ability to type effectively in both traditional and simplified Chinese
Strong written and verbal communication skills
Experience reviewing or annotating linguistic data for technology, media, research, or related projects is advantageous
Comfortable working independently and managing assignments in a remote environment
Reliable ability to meet project quality standards and deadlines
No prior experience in AI training is required
Engagement Details
Independent contractor engagement
Fully remote
Compensation: $20–$35/hour
Work will involve Cantonese and English audio transcription, annotation, automatic-transcript review, timestamping, and linguistic quality assurance
Native-level Cantonese proficiency and strong transcription accuracy are central to this engagement
Experience with traditional and simplified Chinese input is highly relevant
Project workload, timelines, formatting standards, and annotation requirements may vary depending on project needs
Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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