ModelListedExternal

Lahgtna Omnivoice Egyptian v3

Multi-voice Egyptian-Arabic (arz) TTS. v3 continues from v2 on raw, non-diacritized text to fix pronunciation problems caused by MSA diacritics on Egyptian colloquial. It speaks two trained voices (Eqkawkab +...

Sourcehuggingface.co/ehabnegm/lahgtna-omnivoice-egyptian-v3/tree/e859e1f49e2d45eb0d6dfc48e48e03697dfccc65

KindText modelBase modeloddadmix/lahgtna-omnivoice-v2Versionmodel

Model source

Kind: Text model
File size: 2.28 GB
Base model: oddadmix/lahgtna-omnivoice-v2
Version: vmodel
Updated: Sep 21, 2026
Downloads: 79
Tasks: Audio
Source: Hugging Face

Source description

Lahgtna-OmniVoice Egyptian — v3 (multi-voice, non-diacritized)

Multi-voice Egyptian-Arabic (arz) TTS. v3 continues from v2 on raw, non-diacritized text to fix pronunciation problems caused by MSA diacritics on Egyptian colloquial. It speaks two trained voices (Eqkawkab + Noselleel) and clones any reference voice zero-shot. Recommended model for a multi-voice product — best multi-voice intelligibility, best on numbers, and lowest latency (no diacritizer at inference).

👪 Model family

	repo	voices	text	notes
base	lahgtna-omnivoice-v2	—	diacritized	upstream
v1	egyptian	1	diacritized	best CER, single voice
v2	egyptian-v2	2	diacritized	multi-voice
v3 ← you are here	egyptian-v3	2	raw	recommended
🎛️ Compare GUI	Space	—	—	4-model A/B
📚 Data	eqkawkab · noselleel	—	—	~34h

Usage — feed RAW Egyptian text (no diacritics)

import torch, soundfile as sf
from omnivoice.models.omnivoice import OmniVoice
m = OmniVoice.from_pretrained("ehabnegm/lahgtna-omnivoice-egyptian-v3", device_map="cuda", dtype=torch.float16)
audio = m.generate(text="أهلاً بحضرتك، معاك خدمة العملاء، ممكن أساعدك إزاي؟", language="arz",
                   ref_audio="voice.wav", ref_text="نص الكليب المرجعي")
sf.write("out.wav", audio[0], 24000)

Verbalize numbers (e.g. ٢٥ → خمسة وعشرين) and strip/transliterate English words before synthesis (v3 attempts untrained English otherwise).

▶️ Run on Colab

Free GPU, step-by-step: COLAB.md · runnable notebook: lahgtna_colab.ipynb (open it in Colab → Runtime → T4 GPU). Log in with a HF read token (repo is private).

Training

Combined ~34 h, 10,828 clips (Eqkawkab ~8h + Noselleel ~26h), raw + orthography-normalized text. Continued from v2 checkpoint-8000, 5,000 steps, SDPA, bf16, 1× L4.

Benchmark (ASR round-trip CER, 13 pure-Arabic sentences — lower = clearer)

model	CER ↓
v1	0.056	single-voice
v3	0.063	best multi-voice
v2	0.102	multi-voice, diac
base	0.109
v3 beats v2 by ~38% on pure-Arabic — removing the wrong diacritics worked. Full benchmark +
audio: v2 repo `/benchmark`.

321-word long-form stress test

A full Egyptian-Arabic article (~321 words, ~2:50) synthesized by each model, then transcribed back with Whisper large-v3 (ASR round-trip CER — lower = stays on-text).

model	audio	RTF	CER ↓
v3	173 s	0.25	0.21 — stays coherent ✅
base	170 s	0.35	0.69 — drifts ⚠️
v1	170 s	0.35	0.71 — drifts ⚠️
v2	170 s	0.43	0.71 — drifts ⚠️

Finding: on paragraph-length input the diacritized models (base/v1/v2) lose coherence and babble; v3 (non-diacritized) is the only version that stays on-text — decisive for long-form and agent replies. Listen: base.wav, v1.wav, v2.wav, v3.wav.

Audio: long300/.

Limitations & responsible use

Code-switched English is not trained (strip/transliterate it). Audio derived from public YouTube channels (@Eqkawkab, @noselleel) — credit the creators, get permission before commercial use, and don't use the voices to impersonate or mislead.

Latency — time-to-first-chunk (streaming, raw text)

Dropping the diacritizer makes v3 ~250 ms faster than v2 at every setting:

num_step	TTFC
32	1.82 s
16	0.96 s
8 (recommended)	0.54 s
4 (fastest)	0.32 s

Sources

1 source

Hugging FacePrimaryVersion e859e1f49e2d45eb0d6dfc48e48e03697dfccc65

huggingface.co/ehabnegm/lahgtna-omnivoice-egyptian-v3/tree/e859e1f49e2d45eb0d6dfc48e48e03697dfccc65

Verified Sep 21

Model artifacts

1 artifact

model.safetensors

safetensors · 2.28 GB · SHA-256 1cae47470616…2f98 · Hugging Face

Download

Source excerpts

2 excerpts

ReadmeSep 21huggingface.co/ehabnegm/lahgtna-omnivoice-egyptian-v3

--- license: apache-2.0 language: - ar pipeline_tag: text-to-speech library_name: omnivoice base_model: oddadmix/lahgtna-omnivoice-v2 tags: - text-to-speech - tts - arabic - egyptian-arabic - arz - omnivoice - voice-cloning - multi-speaker --- # Lahgtna-OmniVoice Egyptian — **v3** (multi-voice, non-diacritized) Multi-voice **Egyptian-Arabic (`arz`)** TTS. v3 continues from v2 on **raw, non-diacritized text** to fix pronunciation problems caused by MSA diacritics on Egyptian colloquial. It speaks two trained voices (Eqkawkab + Noselleel) and clones any reference voice zero-shot. **Recommended model for a multi-voice product** — best multi-voice intelligibility, best on numbers, and lowest latency (no diacritizer at inference). ## 👪 Model family | | repo | voices | text | notes | |---|---|---|---|---| | base | [lahgtna-omnivoice-v2](https://huggingface.co/oddadmix/lahgtna-omnivoice-v2) | — | diacritized | upstream | | v1 | [egyptian](https://huggingface.co/ehabnegm/lahgtna-omnivoice-egyptian) | 1 | diacritized | best CER, single voice | | v2 | [egyptian-v2](https://huggingface.co/ehabnegm/lahgtna-omnivoice-egyptian-v2) | 2 | diacritized | multi-voice | | **v3** ← you are here | [egyptian-v3](https://huggingface.co/ehabnegm/lahgtna-omnivoice-egyptian-v3) | 2 | **raw** | **recommended** | | 🎛️ Compare GUI | [Space](https://huggingface.co/spaces/ehabnegm/lahgtna-egyptian-tts-compare) | — | — | 4-model A/B | | 📚 Data | [eqkawkab](https://huggingface.co/datasets/ehabnegm/eqkawkab-egyptian-tts) · [noselleel](https://huggingface.co/datasets/ehabnegm/noselleel-egyptian-tts) | — | — | ~34h | ## Usage — feed RAW Egyptian text (no diacritics) ```python import torch, soundfile as sf from omnivoice.models.omnivoice import OmniVoice m = OmniVoice.from_pretrained("ehabnegm/lahgtna-omnivoice-egyptian-v3", device_map="cuda", dtype=torch.float16) audio = m.generate(text="أهلاً بحضرتك، معاك خدمة العملاء، ممكن أساعدك إزاي؟", language="arz", ref_audio="voice.wav", ref_text="نص الكليب المرجعي") sf.write("out.wav", audio[0], 24000) ``` Verbalize numbers (e.g. `٢٥ → خمسة وعشرين`) and **strip/transliterate English words** before synthesis (v3 attempts untrained English otherwise). ## ▶️ Run on Colab Free GPU, step-by-step: **[COLAB.md](./COLAB.md)** · runnable notebook: **[lahgtna_colab.ipynb](./lahgtna_colab.ipynb)** (open it in Colab → Runtime → T4 GPU). Log in with a HF...

NoteSep 21huggingface.co/ehabnegm/lahgtna-omnivoice-egyptian-v3

Source context: 79 downloads · 0 likes · Pipeline text-to-speech · Library omnivoice · Repo ehabnegm/lahgtna-omnivoice-egyptian-v3