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Transcription

Orthography decisions made by people who speak the dialect.

Verbatim and clean-read transcription for Arabic, Algerian Darija, French, Arabic/French code-switching and Tamazight — with a documented, consistent transcription convention.

What we cover

Coverage and categories

Scope any combination below, or bring your own taxonomy — the platform is configured per project.

Modern Standard Arabic

Standard orthography with optional diacritisation.

Algerian Darija

Arabic-script convention (with Arabizi normalisation where required), applied consistently across annotators.

French

Native and Algerian-accented French, verbatim or clean-read.

Arabic/French code-switching

Span-level language tagging so training data reflects how people actually speak.

Tamazight

Kabyle in Latin or Tifinagh script, per your spec. Chaoui, Mozabite and Tuareg on request.

Deliverables

What you receive

  • Time-aligned or utterance-level transcripts
  • Documented orthography and tagging conventions
  • Code-switch span annotation
  • Inter-annotator agreement reporting on a sampled subset

Outcomes

Consistent labels from the first batch to the lastCode-switching your model can actually learn fromTranscripts that match how Algerians write, not textbook Arabic

Typical specification

Output
TXT, JSON, CSV, SRT/VTT
Granularity
Utterance or word-level timings
Tagging
Speaker, noise, code-switch, disfluency
QA
Second-pass review on every batch
Scope this project