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Transcribe Arabic audio into accurate, well-formatted text across single- and multi-speaker recordings and podcasts. Identify speakers when needed, follow project-specific guidelines, and perform annotation/labeling tasks as required. Maintain high accuracy and availability for scheduled shifts.

Review machine-translated content into Finnish by comparing source and translation, making pass/fail quality judgments on accuracy, grammar, and naturalness. Follow guidelines and provide consistent assessments during a one-year, 1–5 hour/week freelance engagement.

Transcribe Portuguese audio into accurate, well-formatted text for single- and multi-speaker recordings, podcasts, and conversations. Identify speakers when applicable, follow project-specific formatting and transcription guidelines, and perform annotation/labeling tasks as needed. Maintain high accuracy and adhere to provided instructions and schedules.

Compare original texts with Traditional Chinese (Taiwan) machine translations to judge accuracy, grammar, and naturalness. Provide simple quality judgments (Pass/Fail or Yes/No) following guidelines. Weekly engagement ~1–5 hours for one year; no rewriting required.

Transcribe Spanish audio into accurate, well-formatted text across single- and multi-speaker recordings and podcasts. Identify speakers when needed, follow project-specific guidelines, and optionally perform annotation/labeling tasks to support training datasets. Maintain quality and meet scheduled shift availability.

Transcribe Indonesian audio into accurate, well-formatted text, identify speakers when needed, follow project-specific guidelines, and perform annotation/labeling tasks as required. Maintain high accuracy and be available for scheduled shifts (minimum 4 hours).

Transcribe Korean audio into accurate, well-formatted text for single- and multi-speaker recordings, podcasts, and conversations. Identify speakers when needed, follow project-specific guidelines, and perform annotation/labeling tasks as required to support audio processing and dataset quality.

Transcribe Danish audio into accurate, well-formatted text; identify speakers; follow project-specific guidelines; optionally perform annotation and labeling to support training datasets.

Freelance contributors will record a scripted conversational session (approx. 1.5 hours) that includes natural Tagalog↔English code-switching. Complete a short Pre-Vet on the Aurora Studio Platform, then, if approved, be matched with another speaker for a scheduled recording. Requires a quiet space and reliable internet.

Convert French audio into accurate, well-formatted written text (single-speaker, podcasts, multi-speaker), identify speakers when applicable, follow project-specific transcription and formatting guidelines, and perform annotation/tagging tasks as required to support audio processing datasets.