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README.md

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+---
+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>

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