Arabic MSA Transcription Evaluator

About The Role

We are currently looking for Arabic language experts and MSA transcription evaluators for a large-scale Modern Standard Arabic (MSA) Transcription Evaluation project. The role involves reviewing AI-generated Arabic transcriptions against audio recordings, making accurate corrections, aligning timestamps, applying proper Arabic punctuation, and following project-specific tagging guidelines. Full project training and onboarding will be provided. Candidates must complete a qualification assessment before starting the project.

• Organization: Loopernode

• Type: Contract

• Location: India , Remote

• Project Duration: Approximately 40 days initially, with potential extension to 60–70+ days

• Commitment: Based on project requirements and assigned workload

• Payment: INR 200/hour, based on actual working time

• Quality Requirement: Minimum 95% accuracy

• Openings: Minimum 50 freelancers

What You'll Do

• Review AI-generated Arabic MSA transcriptions against the original audio.

• Correct transcription errors and ensure accurate text representation.

• Review and correct Arabic grammar, spelling, punctuation, and formatting.

• Perform accurate audio segmentation and timestamp alignment.

• Apply project-specific tags and annotation requirements.

• Identify unclear, inaudible, or ambiguous audio segments according to project guidelines.

• Maintain a minimum quality score of 95%.

• Complete approximately 60 files per day, depending on file complexity.

• Follow detailed project guidelines, training materials, and quality feedback.

Who You Are

• Strong command of Modern Standard Arabic (MSA).

• Minimum B1–B2 Arabic proficiency, with stronger proficiency preferred.

• Strong Arabic reading, writing, listening, and comprehension skills.

• Excellent Arabic typing skills.

• Good understanding of Arabic grammar, spelling, punctuation, and formal language usage.

• Excellent attention to detail and accuracy.

• Ability to identify transcription errors and inconsistencies.

• Able to accurately work with audio segmentation and timestamps.

• Able to follow structured guidelines and apply them consistently.

• Reliable and comfortable working independently.

• Good internet connection and access to a laptop or desktop computer.

Nice to Have

• Previous experience in Arabic transcription or proofreading.

• Experience in linguistic annotation or data labeling projects.

• Familiarity with transcription, audio annotation, or data labeling platforms.

• Background in linguistics, translation, Arabic language studies, or related fields.

• Experience reviewing AI-generated or machine-generated transcriptions.

• Experience working with Arabic MSA audio data.

Training & Selection

• Training: Full project training, guidelines, and platform onboarding will be provided.

• Selection: Candidates must complete an initial qualification assessment before starting the project.

• Assessment Requirement: Candidates must achieve a minimum 95% accuracy score to qualify for production onboarding.

• Assessment Payment: Assessment time will be paid for candidates who achieve 95% accuracy or higher and proceed to production onboarding.

Project Details

• Project Scope: Approximately 600–700 speech hours of Arabic MSA audio.

• Project Duration: Approximately 40 days initially, with potential extension to 60–70+ days.

• Expected Capacity: Approximately 60 files per day per resource.

• Payment: INR 200/hour, based on actual working time spent processing files.

• Quality Requirement: Minimum 95% accuracy.

• Resources Required: Minimum 50 qualified freelancers.

• Equipment: Laptop or desktop computer and reliable internet connection required.

• Payment Schedule: Payment for work completed during a given month will be processed by the end of the following month. Pre-invoices should be submitted by the 10th of the following month.

How to Apply

If you are interested and available for this project, please send your application and relevant details to info@loopernode.in. We will review your application and, if shortlisted, share the qualification assessment, platform onboarding details, and further project information with you.