Building AI Speech for Algerian Darija: Introducing Natiq-dz-ARG

Описание и применение

Natiq-dz-ARG – открытая модель TTS для алжирского дариджи, решающая проблемы естественности речи и кода‑свитчинга, поддерживает клонирование голоса без обучения.

Задача

Existing TTS models produce unnatural speech for Algerian Darija, especially with French code‑switching.

Результат

Natiq-dz-ARG delivers realistic Algerian Darija speech with code‑switching support and zero‑shot voice cloning, enabling developers to integrate local dialect TTS into applications.

Рабочий процесс

• Collect 300+ hours of Algerian speech from 100+ speakers
• Clean and correct mixed‑language transcripts to preserve French words
• Fine‑tune Higgs TTS 3.4B with LoRA on the curated corpus
• Deploy the LoRA adapter on Hugging Face
• Provide a REST API via Natiq Studio for easy integration
• Offer a hosted platform with pre‑built voices and a free token tier

Доказательства

Most text-to-speech (TTS) models today can generate impressive speech in English, French, and Modern Standard Arabic. But what happens when you try generating speech in Algerian Darija?

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Algerian Darija has unique vocabulary, pronunciation patterns, and linguistic influences from Arabic, French, and Amazigh.

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300+ hours of Algerian speech used for fine‑tuning. 100+ speakers to capture different voices, accents, and speaking styles.

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We used Low‑Rank Adaptation (LoRA) to fine‑tune the existing bosonai/higgs-tts-3-4b model.

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The inference process accepts: a reference audio recording, its transcript, and new Darija text to synthesize.

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