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oddadmix/lahgtna-omnivoice-v2

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لهجتنا — Arabic Dialect Text-to-Speech Model

Model Summary

لهجتنا is an open Arabic Text-to-Speech (TTS) model designed to generate natural-sounding speech across Arabic dialects.

The goal of لهجتنا is to create a unified speech model capable of representing spoken Arabic dialects from across the Arab world, capturing their phonetic diversity, rhythm, and prosody.

Unlike many Arabic TTS systems that primarily focus on Modern Standard Arabic (MSA), this model is designed to synthesize real conversational dialect speech.

The model supports Arabic text with diacritics (تشكيل) to improve pronunciation accuracy and speech naturalness.

Model Details

Model Name: لهجتنا Task: Text-to-Speech (TTS) Language: Arabic Dialects Architecture: Based on the OmniVoice

Supported Dialects

The current version of the model includes support for several Arabic dialects, with additional dialects planned as the project evolves.

Dialect Coverage Roadmap

The long-term goal of لهجتنا is to support all Arabic dialects within a single unified model.

Progress will be tracked using the checklist below.

—[x] Egypt
—[x] Saudi Arabia
—[x] Morocco
—[x] Iraq
—[x] Sudan
—[x] Palestine
—[x] Lebanon
—[x] Syria
—[x] Libya
—[x] Tunisia
—[x] Bahrain
—[x] Yemen
—[x] Algeria
—[ ] United Arab Emirates
—[ ] Kuwait
—[ ] Qatar
—[ ] Oman
—[ ] Jordan
—[ ] Mauritania

These checkboxes will be updated as dialect support improves and new datasets are incorporated.

Code Examples

1.https://github.com/Oddadmix/Lahgtna-OmniVoice.git
2.lahgtna-omnivoice-inference | kaggle

This research was supported in part by Lambda, Inc