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README.md

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+---
+library_name: nemo
+license: cc-by-4.0
+language:
+- ar
+pipeline_tag: automatic-speech-recognition
+tags:
+- automatic-speech-recognition
+- asr
+- arabic
+- arabic-asr
+- dialectal-arabic
+- gulf-arabic
+- fastconformer
+- ctc
+- efficient
+---
+
+<div align="center">
+
+<img src="logo.png" width="180"/>
+
+# lemura-arabic-asr
+
+![Format](https://img.shields.io/badge/Format-NeMo-0b7285?style=flat) ![Task](https://img.shields.io/badge/Task-Speech%20Recognition-5f3dc4?style=flat) ![Type](https://img.shields.io/badge/Type-ASR-862e9c?style=flat) ![License](https://img.shields.io/badge/License-cc--by--4.0-6c757d?style=flat)
+
+
+**A compact, dialect-aware Arabic speech-recognition model — leaderboard-tier accuracy at ~18× fewer parameters.**
+
+![Task](https://img.shields.io/badge/task-ASR-blue?style=flat) ![Params](https://img.shields.io/badge/params-~115M-f59e0b?style=flat) ![Architecture](https://img.shields.io/badge/arch-FastConformer--CTC-6f42c1?style=flat) ![Dialects](https://img.shields.io/badge/dialects-MSA%20%2B%204%20groups-brightgreen?style=flat) ![Runtime](https://img.shields.io/badge/runtime-CPU%20%C2%B7%20GPU%20%C2%B7%20real--time-blue?style=flat)
+[ Overview](#-overview) · [ Model Details](#-model-details) · [ Benchmarks](#-benchmarks) · [ Efficiency](#-efficiency) · [ Usage](#-usage) · [ Live Demo](https://huggingface.co/spaces/lemuralabs/lemura-arabic-asr-demo)
+
+</div>
+
+---
+
+## Overview
+
+**lemura-arabic-asr** is a compact multi-dialect Arabic ASR model built for accuracy *and* efficiency. It is a **FastConformer-CTC** acoustic model (\~115M parameters), adapted in-house from the NVIDIA FastConformer foundation and fine-tuned on **\~2,900 hours** of Arabic spanning **MSA** and the **Gulf, Egyptian, Levantine, and Maghrebi** dialect groups.
+
+**Highlights**
+
+- **Small & fast** — ~115M parameters; runs comfortably on **CPU** and in **real time**, no GPU required.
+- **Dialect-aware** — trained across five Arabic dialect groups, not MSA-only.
+- **Robust on real audio** — strongest on broadcast, conversational, and Gulf/MSA speech.
+- **Open & simple** — a single `.nemo` file, loadable in a few lines with NVIDIA NeMo.
+
+## Model Details
+
+| | |
+|---|---|
+| **Model** | lemura-arabic-asr — compact multi-dialect Arabic ASR |
+| **Task** | Automatic speech recognition (audio → text) |
+| **Architecture** | FastConformer encoder + CTC decoder |
+| **Parameters** | ~115M |
+| **Foundation** | Adapted from NVIDIA FastConformer; ~2,900 h Arabic fine-tuning |
+| **Audio input** | 16 kHz mono (auto-resampled) |
+| **Languages** | Arabic — MSA + Gulf / Egyptian / Levantine / Maghrebi |
+| **Runtime** | NVIDIA NeMo — CPU · GPU · real-time |
+| **License** | CC-BY-4.0 |
+
+## Benchmarks
+
+Evaluated on all six **Open Universal Arabic ASR Leaderboard** test sets using the [official leaderboard code](https://github.com/Natural-Language-Processing-Elm/open_universal_arabic_asr_leaderboard) (same normalizer, same WER metric).
+
+### Per-set WER (%)
+
+| SADA | Common Voice 18 | MASC-clean | MASC-noisy | MGB-2 | Casablanca | **Average** |
+|---:|---:|---:|---:|---:|---:|---:|
+| 37.28 | 9.74 | 7.27 | 23.65 | 14.33 | 58.24 | **25.08** |
+
+### In context (Average WER %, lower is better)
+
+| Model | Params | Avg WER |
+|---|---:|---:|
+| cohere-transcribe-arabic-07-2026 | ~2.0B | 25.87 |
+| **lemura-arabic-asr** | **~0.12B** | **25.08\*** |
+| omniASR_LLM_7B | 7B | 28.32 |
+| Qwen3-Omni-30B-A3B | 30B | 30.71 |
+| nvidia-conformer-ctc-large-arabic (lm) | 0.6B | 32.91 |
+| Qwen3-ASR-1.7B | 1.7B | 33.36 |
+
+## Efficiency
+
+The top leaderboard systems are large generative audio-LLMs (2–30B parameters) that need GPUs. lemura-arabic-asr reaches a comparable accuracy tier with a **~115M-parameter** CTC model:
+
+| | lemura-arabic-asr | Typical top systems |
+|---|---|---|
+| Parameters | **~115M** | 2B – 30B |
+| Hardware | **CPU or GPU** | GPU |
+| Latency | **Real-time** | Seconds / clip |
+| Footprint | **~0.4 GB** | 4 – 60 GB |
+
+That makes it practical for **on-device, low-cost, and high-throughput** Arabic transcription where the big models are impractical.
+
+## Usage
+
+```python
+import nemo.collections.asr as nemo_asr
+
+model = nemo_asr.models.ASRModel.restore_from("asr_final.nemo")
+print(model.transcribe(["audio.wav"])) # 16 kHz mono
+```
+
+Try it live — no install: **[ lemura-arabic-asr demo](https://huggingface.co/spaces/lemuralabs/lemura-arabic-asr-demo)**
+
+## Credits
+
+- Acoustic foundation: **NVIDIA FastConformer**
+- Evaluation: the **[Open Universal Arabic ASR Leaderboard](https://github.com/Natural-Language-Processing-Elm/open_universal_arabic_asr_leaderboard)** official code

asr_final.nemo

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