
Farah I.
Somali Linguist
Habilidades

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Portfólio
Experiência profissional
Somali Linguistic QC Specialist, MTPE Editor and Data Annotator
Lionbridge • Freelance
Dec 2024 - Present • 1 yr 9 mos
Performed English to Somali machine translation post-editing, linguistic quality review, data annotation, and language quality control for AI and language technology projects. Reviewed and corrected machine-generated Somali content for meaning, fluency, terminology, grammar, cultural appropriateness, and dialect consistency. Completed linguistic annotation and quality review tasks while following detailed project guidelines and maintaining high accuracy. Delivered 372,000+ words of MTPE and contributed to 220+ hours of audio-related language data work, maintaining approximately 98.8% alignment accuracy.
Not Found
Freelance • 6 yrs 2 mos
Somali Subtitle Translator and Localization Specialist
Dec 2023 - Present • 2 yrs 9 mos
Provided English to Somali audiovisual localization and subtitle translation for digital content, with a focus on natural language, cultural accuracy, timing, and readability. Translated and reviewed subtitle files while maintaining correct terminology, tone, register, and meaning across Somali audiences. Worked with SRT and VTT subtitle formats and performed subtitle quality checks for timing, segmentation, spelling, punctuation, and consistency. Adapted dialogue and on-screen content to sound natural in Somali rather than relying on literal translation. Delivered localization work according to project specifications, deadlines, and quality requirements.
Linguistic Quality Reviewer and Transcription QC Specialist
Apr 2023 - Present • 3 yrs 5 mos
Provided Somali linguistic quality review, transcription quality control, language data annotation, and content evaluation for AI and language technology projects. Reviewed more than 350 hours of Somali audio and evaluated 45,000+ language and prompt strings for accuracy, naturalness, consistency, and compliance with project guidelines. Identified transcription and linguistic errors and applied corrections while maintaining approximately 99% accuracy across assigned quality review work.