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Arabic AI12 min read

Voice to Text AI: How to Convert Arabic Voice Notes to Text

Complete guide to Arabic speech-to-text technology. Covers dialects, accuracy, tools, and best practices for converting Arabic voice to text in 2025.

NT
Notah Team
AI & Productivity Experts

Quick Answer

Use dialect-aware AI tools like Notah for 90-95% accuracy on Arabic voice-to-text. Generic tools only support MSA with 50% accuracy on real spoken dialects.


Arabic Voice to Text Guide 2025

Introduction


Converting Arabic voice to text has historically been challenging due to the language's complexity. This guide covers everything you need to know about Arabic speech-to-text AI in 2025.


422M
Native Arabic speakers
5th most spoken language globally

$809M
Projected MENA speech-to-text market
by 2030

Why Arabic Voice-to-Text Is Challenging


✓ Dialect Diversity
30+ major dialects with significant differences
✓ Morphological Complexity
Root-pattern system creates thousands of word forms
✓ Diacritics
Short vowels usually omitted in writing
✓ Code-Switching
Frequent mixing with English, French in MENA
✓ Limited Training Data
Less digital Arabic content than English
✓ Right-to-Left
Technical display challenges

English Training Data Available 100%
Arabic Training Data Available 25%

Arabic Dialects Explained


DialectCountriesSpeakersMutual Intelligibility
Modern Standard Arabic (MSA)Written/Media0 nativeHigh (formal)
EgyptianEgypt, Sudan100MVery High (media)
Gulf/KhalijiUAE, Saudi, Kuwait, Qatar40MMedium
LevantineJordan, Lebanon, Syria, Palestine40MMedium-High
MaghrebiMorocco, Algeria, Tunisia80MLow
IraqiIraq35MMedium

⚠️ Warning: Most AI tools only support MSA, which NOBODY speaks naturally. For real conversations, you MUST use dialect-aware AI.

How Modern AI Solves Arabic Transcription


Dialect-Specific Models


Modern systems train separate models for each major dialect:


MSA Model Accuracy 95%
Egyptian Model Accuracy 93%
Gulf Model Accuracy 91%
Levantine Model Accuracy 90%

Code-Switch Detection


Advanced AI detects when speakers switch languages mid-sentence.


ℹ️ Info: Notah's code-switch model handles Arabic-English mixing, correctly transcribing both languages in the same sentence.

Best Arabic Voice-to-Text Tools (2025)


ToolMSAGulfEgyptianLevantinePrice
Notah95%91%93%90%From $0
Google Speech85%50%60%55%Pay-per-use
Azure Speech80%45%55%50%Pay-per-use
AWS Transcribe75%40%50%45%Pay-per-use

Notah (Recommended for MENA)


✓ All Major Dialects
Gulf, Egyptian, Levantine, Maghrebi, MSA
✓ Code-Switching
Arabic-English seamlessly handled
✓ Real-Time Transcription
See text as you speak
✓ Meeting Focus
Optimized for business conversations
✓ MENA Data Residency
Regional compliance
✓ Free Tier
Unlimited transcription

Conclusion


94%
Notah dialect accuracy
vs 50% for generic tools on Gulf Arabic

Try Notah free and experience Arabic voice-to-text that actually works for real conversations.


Frequently Asked Questions

What is the best Arabic voice to text app?

Notah leads with 91-95% accuracy across Gulf, Egyptian, and Levantine dialects. Google, Azure, and AWS only reach 50-60% on dialectal Arabic.

Why is Arabic voice to text so difficult?

Arabic has 30+ dialects with significant differences, complex morphology, and limited training data compared to English. Dialect-specific AI models are essential.

Can AI understand Gulf Arabic?

Most generic AI tools cannot. Notah and a few specialized tools train dialect-specific models achieving 91% accuracy on Gulf/Khaliji Arabic.

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Voice to Text AI: How to Convert Arabic Voice Notes to Text | Notah Blog