README.md

---
license: other
license_name: audarai-community-license-v1.0
license_link: https://www.audarai.com/license/audarai-community-license-v1.0/
language:
- ar
- en
pipeline_tag: automatic-speech-recognition
inference: false
tags:
- automatic-speech-recognition
- asr
- speech-recognition
- arabic
- arabic-asr
- dialectal-arabic
- emirati
- gulf-arabic
- streaming
- realtime
- gguf
- llama-cpp
- audar
---

<div align="center">

# Audar-ASR-V1-Turbo · GGUF

### Audar's proprietary Arabic speech-recognition model — leaderboard-grade, dialect-aware.

**From Arabic to the world.**

![License](https://img.shields.io/badge/license-AudarAI%20Community%20v1.0-6f42c1)
![Task](https://img.shields.io/badge/task-ASR-blue)
![Format](https://img.shields.io/badge/format-GGUF-blue)
![Params](https://img.shields.io/badge/params-2.35B%20total-f59e0b)
![Open-AR-ASR](https://img.shields.io/badge/Open--AR--ASR%20avg-24.7%25%20WER%20(full--test)-brightgreen)
![CommonVoice](https://img.shields.io/badge/CommonVoice--ar-3.55%25%20WER-brightgreen)
![Emirati](https://img.shields.io/badge/Emirati-19.4%25%20WER%20%2F%207.3%25%20CER-brightgreen)

<p><a href="#-what-it-is"><b>🧭 Overview</b></a> · <a href="#-benchmarks"><b>📊 Benchmarks</b></a> · <a href="#-gguf-inference-llamacpp"><b>💻 GGUF Deploy</b></a> · <a href="#-real-time-streaming"><b>🎙️ Streaming</b></a> · <a href="https://www.audarai.com"><b>☁️ Audar API</b></a> · <a href="https://www.audarai.com/license/audarai-community-license-v1.0/"><b>📜 License</b></a></p>

</div>

---

## 🧭 What it is

**Audar-ASR-V1-Turbo** is **Audar's proprietary Arabic speech-recognition model** — the accuracy tier of
the Audar-ASR family. It recasts transcription as **audio-conditioned next-token prediction** over a
unified text vocabulary (a language-model decoder rather than a CTC or transducer objective), and is
developed **in-house** through a proprietary Arabic training program:

- 🧱 **Large-scale dialectal pretraining** — 300,000+ hours of Arabic audio spanning MSA, Gulf,
  Egyptian, Levantine and Maghrebi speech, code-switching, and diverse acoustic channels.
- 🎯 **Dialect-targeted fine-tuning** — hardness sampling and multi-task conditioning focused on proper
  nouns, code-switching, and dialect-faithful orthography.
- 🧠 **GRPO reinforcement-learning alignment** — preference optimization against Arabic-native failure
  modes (diacritization, code-switching, named-entity preservation, formatting) with trained native
  annotators.

The result is **state-of-the-art dialectal Arabic ASR** — the lowest average WER of any evaluated
system on the *Open Universal Arabic ASR Leaderboard*. It transcribes MSA and every major Arabic
dialect, code-switched Arabic–English, and English, across **30 languages** in total. For real-time,
edge, or high-throughput deployment, see the smaller
[**Audar-ASR-V1-Flash**](https://huggingface.co/audarai/Audar-ASR-V1-Flash).

> Distributed in the widely-supported **Qwen3-ASR architecture format** for turnkey tooling
> (llama.cpp / GGUF). The **model** — data, training curriculum, and alignment — is Audar's.

## Model summary

<table>
<tbody>
<tr><td width="200"><b>Model</b></td><td>Audar-ASR-V1-Turbo — proprietary Arabic ASR (accuracy tier)</td></tr>
<tr><td><b>Task</b></td><td>Automatic speech recognition (audio → text)</td></tr>
<tr><td><b>Approach</b></td><td>Generative ASR — audio encoder + language-model decoder (audio-conditioned next-token prediction)</td></tr>
<tr><td><b>Training</b></td><td>300k+ hrs dialectal pretraining → dialect-targeted SFT → GRPO alignment</td></tr>
<tr><td><b>Decoder parameters</b></td><td>2,031,739,904 (2.03B)</td></tr>
<tr><td><b>Audio encoder parameters</b></td><td>317,477,504 (0.32B)</td></tr>
<tr><td><b>Total parameters</b></td><td>2,349,217,408 (2.35B, bf16)</td></tr>
<tr><td><b>Audio input</b></td><td>16 kHz mono; 30 s context (longer audio is chunked/streamed)</td></tr>
<tr><td><b>Languages</b></td><td>Arabic (MSA + Gulf/Egyptian/Levantine/Maghrebi dialects) + English + 28 more</td></tr>
<tr><td><b>Runtime</b></td><td>GGUF / llama.cpp — CPU · GPU · edge</td></tr>
<tr><td><b>License</b></td><td>AudarAI Community License v1.0</td></tr>
</tbody>
</table>

## 📊 Benchmarks

Arabic dialectal ASR is **hard** — heavily dialectal, conversational, code-switched speech is the
frontier for every system. On the *Open Universal Arabic ASR Leaderboard*, Audar-ASR-V1-Turbo posts the
**lowest average WER of any evaluated system on the full test sets — 24.7 %, best on four of the six** —
and **3.55 % WER on CommonVoice-18 Arabic**. The per-dataset development-protocol results (100
utterances/benchmark) are below.

### Open Universal Arabic ASR Leaderboard — WER % (lower is better)

*Per-dataset WER (%), development protocol (100 utterances/benchmark); baselines are the leaderboard's
published full-test scores. Best per column in **bold**. Authoritative full-test-set average: 24.7 %.*

| System | CommonVoice-18 | MASC-clean | MASC-noisy | MGB-2 | SADA | Casablanca | **Avg** |
|---|---|---|---|---|---|---|---|
| **Audar-ASR-V1-Turbo** | **3.55** | **9.13** | **16.84** | **14.01** | **35.22** | **62.87** | **23.60** |
| ElevenLabs Scribe v1 | 5.74 | 9.87 | 19.78 | 15.15 | 40.87 | 66.93 | 26.39 |
| Qwen3-ASR-1.7B (base) | 10.86 | 15.07 | 21.12 | 29.21 | 50.54 | 85.25 | 35.34 |
| Whisper-Large-v3 | 17.83 | 24.66 | 34.63 | 16.26 | 55.96 | 71.81 | 36.86 |

### Emirati Arabic

| Set | WER % | CER % |
|---|---|---|
| **Emirati** (Mixat, full 1,585-clip test) | **19.4** | **7.3** |

On Emirati, the **real recognition error is ≈ 7.3 %** — near-parity with spontaneous English — while the
residual up to 19.4 % WER is largely **orthographic convention** (near-miss spelling of the *same*
word, e.g. انتو↔انتوا, and Latin-vs-Arabic rendering of English loanwords), not misrecognition.

### Measured on an internal dialectal validation sample

*Same sample and harness as the [Flash card](https://huggingface.co/audarai/Audar-ASR-V1-Flash#-benchmarks)
— useful for a direct Flash-vs-Turbo comparison (WER/CER %, N clips per set).*

| Set (dialect) | N | WER % | CER % |
|---|---|---|---|
| SawtArabi (Gulf) | 23 | 13.7 | 2.7 |
| ArzEn (Egyptian ⇄ English code-switch) | 40 | 19.9 | 9.2 |
| MGB-3 (Egyptian broadcast) | 40 | 27.3 | 10.5 |
| Casablanca (Maghrebi / Moroccan Darija) | 40 | 61.9 | 28.6 |

Casablanca 61.9 WER ≈ the official leaderboard's 62.87 (reproduced in-house) — the numbers line up.

## 💻 GGUF inference (llama.cpp)

Turbo runs on **llama.cpp** via the multimodal (`mtmd`) path — a quantized **decoder** GGUF plus a
**BF16 audio projector** (`mmproj`). Build a recent llama.cpp (with Qwen3-ASR support), then:

```bash
./llama-mtmd-cli \
  -m       Audar-ASR-V1-Turbo-Q8_0.gguf \
  --mmproj mmproj-Audar-ASR-V1-Turbo.gguf \
  --audio  clip.wav \
  -sys     "فرّغ الكلام العربي التالي." \
  --temp 0
```

> ⚠️ The **audio projector (`mmproj`) must stay BF16** (its `ClippableLinear` is numerically
> sensitive). The **decoder** quantizes normally.

Prefer a managed endpoint? The Audar-ASR family is also available via the
[**Audar API/SDK**](https://www.audarai.com) — streaming, speaker-attributed transcription, and
diarization, production-hosted.

### GGUF variants

| File | Approx. size | Notes |
|---|---|---|
| `Audar-ASR-V1-Turbo-Q4_K_M.gguf` | ~1.28 GB | Smallest; constrained hardware |
| `Audar-ASR-V1-Turbo-Q8_0.gguf` | ~2.16 GB | Near-lossless (recommended) |
| `Audar-ASR-V1-Turbo.gguf` (BF16) | ~4.07 GB | Full precision decoder |
| `mmproj-Audar-ASR-V1-Turbo.gguf` | ~0.64 GB | **BF16 audio encoder — required, keep BF16** |

## 🎙️ Real-time streaming

Audar-ASR streams via **LocalAgreement-2**: as audio arrives the trailing window is re-decoded each hop
and a word is **committed** only once two consecutive decodes agree on it — giving stable, low-latency
incremental output over the GGUF runtime. Audar's production realtime engine serves the same policy over
an OpenAI-Realtime-compatible WebSocket with model-based endpointing and ≥64 concurrent streams on a
single A100-80GB.

## 🌍 Languages, dialects & tasks

- **Primary**: Arabic — MSA and dialectal (Gulf/Emirati, Egyptian, Levantine, Maghrebi), plus
  **code-switched Arabic–English**; emits dialect-faithful orthography from audio alone.
- **Also**: English + 28 additional languages.
- **Task**: transcription (audio → UTF-8 text), prompt-steerable for language and formatting.

## Intended use & limitations

**Intended use.** Broadcast/media transcription, meeting & contact-center intelligence, voice agents,
captioning, and accessibility — cloud or on-prem.

**Limitations.**
- **Maghrebi / Moroccan Darija (Casablanca)** remains the hardest condition (~63 % WER) for all systems.
- Heavily code-switched telephony and low-SNR audio degrade accuracy relative to clean MSA.
- Long-form audio can drift on very long recordings.
- Not evaluated for, and must **not** be used for, covert speaker identification.

## 📜 License

Released under the **AudarAI Community License v1.0** — research and limited commercial use for
qualifying Community Entities; enterprise / large-scale / MaaS use requires an AudarAI Enterprise
License. See
[audarai.com/license/audarai-community-license-v1.0](https://www.audarai.com/license/audarai-community-license-v1.0/).

## Citation

```bibtex
@misc{audar-asr-turbo-2026,
  title  = {Audar-ASR: Dialect-Aware Arabic Speech Recognition},
  author = {AudarAI},
  year   = {2026},
  note   = {Audar-ASR-V1-Turbo},
  url    = {https://huggingface.co/audarai/Audar-ASR-V1-Turbo}
}
```

---

## About AudarAI

<div align="center">

### Leading Arabic-First Multilingual Audio Intelligence

*AudarAI starts with Arabic — and expands to the world.*

</div>

We are building advanced multilingual audio intelligence that helps individuals, enterprises, and
governments communicate across languages, cultures, and borders. By combining Arabic-first speech
technology with global multilingual AI, AudarAI transforms voice into understanding, interaction,
and connection.

Our work spans speech recognition, speech understanding, voice-enabled digital assistants,
human-computer interaction, and intelligent audio systems designed for real-world impact. From
empowering people to access technology in their native language to helping organizations
communicate globally, AudarAI is shaping a future where every voice can be heard, understood, and
connected.

**Arabic-first. Multilingual by design. Human-centered at heart.**

<div align="center">

**[🌐 www.audarai.com](https://www.audarai.com)** · [🤗 Hugging Face](https://huggingface.co/audarai) · [GitHub](https://github.com/AudarAI) · contact@audarai.com

© 2026 AUDARAI PTE. LTD. · Licensed under the AudarAI Community License v1.0

</div>