Sawt - صوت

Introduction to Sawt - صوت

Sawt is an AI-powered text-to-speech platform designed exclusively for the Arabic language. It addresses the linguistic complexity of Arabic by supporting both Modern Standard Arabic (MSA) and a wide range of regional dialects, enabling natural and contextually appropriate speech synthesis. The platform serves content creators, educators, marketers, developers, and accessibility professionals who require high-fidelity Arabic audio output for diverse applications.

Unlike general-purpose TTS systems, Sawt is built from the ground up with Arabic phonology, morphology, and sociolinguistic variation in mind. Its architecture incorporates specialized models for diacritization, prosody, and dialect-specific pronunciation rules—ensuring accurate rendering of tashkeel, vowel length, emphatic consonants, and dialectal lexical and syntactic features.

Key Takeaways

• Supports 17+ Arabic dialects including Egyptian, Saudi, Gulf, Levantine, Moroccan, Algerian, Tunisian, Jordanian, Lebanese, Qatari, Kuwaiti, and North African variants
• Offers 73+ distinct voices—male and female—with usage-specific voice profiles (e.g., narration, advertising, education, conversation)
• AI-powered automatic diacritization (tashkeel) that adds precise harakat to unvoweled Arabic text for correct pronunciation
• Voice expression control enabling manual or AI-assisted insertion of emotional and prosodic cues (e.g., joyful, solemn, excited, whispering, shouting)
• Integrated text editing suite with dialect conversion, grammar and orthographic correction, summarization, paraphrasing, and AI-generated text
• Audio post-processing tools including trimming, playback speed adjustment, and export in MP3 and WAV formats
• Real-time generation workflow: paste text, select voice and dialect, and generate audio in seconds

How Sawt Works

Sawt operates through a three-stage workflow accessible via its web interface. First, users input Arabic text into the intelligent editor, which supports full Unicode Arabic script and offers on-the-fly tools—including dialect translation, AI-based diacritization, grammatical correction, and style-based paraphrasing. Second, users select a voice from the curated library using filters for gender, dialect, and use case (e.g., "Egyptian — Advertising", "Levantine — Conversation"). Each voice includes a preview audio sample. Third, users optionally apply voice expressions or adjust audio parameters before generating and exporting the final audio file.

The underlying technology combines neural TTS models fine-tuned per dialect and use case, coupled with rule-based and ML-driven Arabic NLP components for text normalization, tokenization, and prosodic annotation. Diacritization leverages a dedicated transformer model trained on annotated MSA and dialectal corpora, while expression tagging uses contextual semantic analysis to recommend appropriate prosodic markers.

Core Benefits and Applications

Sawt enables practical, production-grade Arabic speech synthesis across multiple domains. In education, it supports language learning materials, audiobooks, and accessible course content with accurate MSA and dialectal pronunciation. For marketing and media, it powers multiregional ad campaigns, social media voiceovers (e.g., Moroccan Arabic for Instagram Reels, Gulf Arabic for YouTube ads), and podcast intros. Content creators use it for narrating blogs, generating voiceovers for explainer videos, and building interactive conversational interfaces. Developers integrate it via API for accessibility features in apps and websites. Additionally, researchers and linguists benefit from its dialect coverage and reproducible, high-quality synthetic speech for annotation and evaluation tasks.