leva-tts

mohammedaly22/leva-tts

leva-tts is a text-to-speech model from mohammedaly22. Use it when you need text read aloud. It is set up for coqui. The card lists the license as cc-by-nc-4.0.

<div align="center" <img src="https://huggingface.co/mohammedaly22/leva-tts/resolve/main/docs/LevaTTS-Banner-Image.png" alt="Leva-TTS — Levantine Arabic ⇄ English Text-to-Speech" width="100%" </div

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.pth5.6 GB · 100%

At a glance

Task: Text-to-Speech
Library: coqui
License: cc-by-nc-4.0
Access: Public
Created: May 31, 2026
Updated: Jun 10, 2026
SHA: 7f1200e9

Base models

coqui/XTTS-v2

Datasets

mohammedaly22/lahgtna-levantine-tts

Spaces

mohammedaly22/Levantine-Zero-Shot-TTS

Model card

From the Hugging Face model README

🌿 Leva-TTS — Low-Latency Code-Switching TTS (Levantine Arabic ⇄ English)

A production-oriented Levantine Text-to-Speech model — a fine-tuned XTTS-v2 optimized for real-time conversational agents.

🎯 KPI	Target	Measured	Status
Peak VRAM (inference)	≤ 3 GB	2.13 GB	✅
Time-to-First-Audio (p50)	< 300 ms	565 ms	⚠️
Real-Time Factor (RTF)	< 0.3	0.21	✅
Streaming output	required	chunked PCM + WS	✅

</div>

Leva-TTS is a text-to-speech model for Levantine Arabic / English code-switching, built by fine-tuning XTTS-v2 on 50,000 synthetic utterances generated with Lahgtna-OmniVoice v2. It handles natural intra-sentence switching between Levantine dialect and English, supports 10 built-in speakers and zero-shot voice cloning, and offers a streaming generator for low-latency conversational use.

Base model: coqui/XTTS-v2 (GPT autoregressive backbone + HiFi-GAN decoder)
Languages: Levantine Arabic (ar), English (en), and code-switch mixes
Sample rate: 24 kHz
Speakers: Badr, Mohamed, Saad, Rami, Fadi (M) · Amina, Fatma, Lamyaa, Mona, Haneen (F)

✨ Key Features

Feature	Details
🗣️ Natural code-switching	Intra-sentence Arabic ↔ English
⚡ Streaming output	First audio chunk < 300 ms
💾 Low VRAM	≤ 3 GB at inference
🌿 Levantine dialect	ق→/ʔ/ glottal, ج→/ʒ/, il- article, b- prefix
🔤 Smart text front-end	Partial diacritics on homographs + Levantine lexicon
👥 10 speakers	5 male + 5 female, diverse Levantine accents
📡 WebSocket streaming	FastAPI server with real-time chunked PCM
🔌 Pipecat ready	Drop-in `TTSService` for voice agents

🚀 Quick start (pip)

conda create -n leva-tts python=3.10 -y && conda activate leva-tts
sudo apt-get install -y espeak-ng ffmpeg libsndfile1

# Install PyTorch first so pip locks a CUDA build matching your GPU driver.
# (torch >= 2.9 ships CUDA-13 wheels that fail on common CUDA-12.x drivers.)
pip install torch==2.3.0 torchaudio==2.3.0 --index-url https://download.pytorch.org/whl/cu121

pip install leva-tts

Leva-TTS uses the maintained coqui-tts fork (same TTS/XTTS modules); the unmaintained TTS package pins numpy==1.22.0 and cannot resolve on modern Python. A plain pip install leva-tts resolves cleanly.

from leva_tts import LevaTTS, SPEAKERS
import soundfile as sf

tts = LevaTTS(device="cuda", preprocess_text=True, verbose=False)
# auto-downloads this checkpoint + the 10 reference speakers on first use

# 1) Built-in speaker  (speaker must be one of SPEAKERS, else ValueError)
wav, sr = tts.synthesize("هَلَّق أنا عم أشتغل على the project",
                         speaker="Badr", temperature=0.65)
sf.write("out.wav", wav, sr)            # sr == 24000

# 2) Zero-shot voice cloning (your own 3–10 s clip)
wav, sr = tts.zero_shot_synthesize("والله the meeting كانت important كتير",
                                   "my_voice.wav")

# 3) Streaming generators
for chunk in tts.stream("بِدِّي أحكيلك عن the new feature", speaker="Amina"):
    ...                                  # play / forward each chunk
for chunk in tts.zero_shot_stream("هلق عم نشتغل", "my_voice.wav"):
    ...

Generation parameters (optional, per-call on every method): temperature, length_penalty, repetition_penalty, top_k, top_p, speed.

For the FastAPI streaming server, Pipecat integration, the Gradio demo, evaluation and fine-tuning, clone the repo: 👉 https://github.com/MohammedAly22/Leva-TTS

📦 Files in this repo

File	Description
`best_model.pth`	Fine-tuned XTTS-v2 checkpoint (GPT + decoder)
`config.json`	XTTS-v2 config
`reference_audios/`	The 10 built-in speaker reference clips + `references.json`
`sample_wavs/`	Audio sample comparisons (Base XTTS-v2 vs Lahgtna v2 vs Leva-TTS)

Manual download: huggingface-cli download mohammedaly22/leva-tts

🎵 Audio samples — Model comparison

Click a sentence to expand and play the three models. Progression: Base XTTS-v2 → Lahgtna v2 → Leva-TTS.

🔀 Code-switching (Levantine + English)

<details open> <summary>هَلَّق أنا عم أشتغل على the new project اللي حكيتلك عنه — <b>Badr (M)</b></summary>

Base XTTS-v2