Arabic (MSA) Spontaneous Dialogue
Two-party spontaneous conversations in Modern Standard Arabic capture natural dialogue patterns and turn-taking. Human-verified transcripts with utterance-level timestamps make the corpus suitable for ASR, conversational AI, and multilingual speech model development.
Dataset Overview
Commercial License
Cleared for production AI development and model training.
Native Speakers
Native Arabic speakers covering Modern Standard Arabic.
Human Verified
Human transcription with review, reviewed before delivery.
Production Ready
16 kHz / 16-bit PCM WAV with structured, validated metadata.
Hear the data before you license it.
A representative audio excerpt from this dataset. Full transcripts and speaker metadata are delivered with licensed data.
Audio Sample 1
25–34 · Modern Standard Arabic
Built to a documented standard.
Every delivery matches the recording, audio, and annotation specification below.
Recording
Two-party conversational recordings in quiet indoor environments.
Audio
Annotation
- Human Transcript
- Speaker ID
- Timestamps
- JSONL / TXT
Utterance-level timestamps
Balanced, documented speaker coverage.
Native Arabic speakers
Balanced
18–60
Modern Standard Arabic
Verified at every stage of delivery.
What teams build with this dataset.
Automatic Speech Recognition
Train and benchmark ASR models against human-verified reference transcripts.
Voice Agents
Build voice assistants that hold up against real conversational speech.
Multilingual AI Products
Extend language coverage with consistent annotation across locales.
License this dataset for production AI.
Commercial licensing for production AI development. Terms are shared on request; evaluate representative samples before purchase.