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Perle is seeking expert Tunisian Arabic transcribers to convert audio recordings into precise, time-aligned transcripts following our project-specific style guide. You will handle speaker identification, code-switching, disfluencies, and non-speech events, delivering high-quality output for AI lab applications.
Ideal candidates are native in Tunisian Arabic with strong Modern Standard Arabic, French familiarity for loanwords, and at least two years of transcription or related experience.
Perle is seeking expert Tunisian Arabic transcribers to convert audio recordings into precise, time-aligned transcripts following our project-specific style guide. You will handle speaker identification, code-switching, disfluencies, and non-speech events, delivering high-quality output for AI lab applications.
Ideal candidates are native in Tunisian Arabic with strong Modern Standard Arabic, French familiarity for loanwords, and at least two years of transcription or related experience.