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Rawda Morad

@rawdamorad

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Arabic AI Trainer at RWS who annotated 500+ hours of Arabic audio with 100% transcription accuracy.

Egypt

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At RWS, I annotate and transcribe Arabic audio for ASR and TTS model training. I’ve worked on more than 500 hours of MSA and Egyptian Arabic audio, achieving 100% linguistic accuracy.

I also review AI-generated transcripts and label Arabic text for NLP tasks, including sentiment analysis and named entity recognition. My work includes phonetic transcription, audio segmentation, and linguistic QA, with 97%+ quality scores.

Experience

Work history, roles, and key accomplishments

Current

Arabic Voice Data Annotator & Transcription Specialist

Current

RWS

Jan 2026 - Present (9 months)

Annotated and transcribed 500+ hours of Arabic audio for ASR/TTS model training, achieving 100% linguistic accuracy. Reviewed and corrected AI-generated transcripts, achieving 97%+ quality scores, and created annotation guidelines.

Education

Degrees, certifications, and relevant coursework

Ismailia National University

Bachelor of Medical Laboratory Sciences, Medical Laboratory Sciences

2024 -

Pursuing a Bachelor of Medical Laboratory Sciences with expected completion in 2028. Coursework includes data analysis, research methodology, quality assurance, and technical documentation.

RWS

AI Voice Data Annotation & Speech Technology Training, AI Voice Data Annotation and Speech Technology

2026 - 2026

Completed AI Voice Data Annotation and Speech Technology Training covering ASR data preparation, phonetic transcription, timestamping, and QA protocols.