| --- |
| language: |
| - fa |
| license: apache-2.0 |
| library_name: nemo |
| pipeline_tag: automatic-speech-recognition |
| base_model: |
| - Reza2kn/Shenava-Rizeh-v1.0 |
| base_model_relation: finetune |
| tags: |
| - automatic-speech-recognition |
| - speech |
| - persian |
| - farsi |
| - fastconformer |
| - ctc |
| - streaming |
| - on-device |
| - shenava |
| - shenava-1 |
| - visualears |
| - nemo |
| - distillation |
| metrics: |
| - wer |
| - cer |
| datasets: |
| - Reza2kn/visualears-persian-asr-16k |
| - Reza2kn/visualears-golden-6669 |
| - Reza2kn/fleurs-fa-benchmark |
| --- |
| |
| # 🐣🎙️ Shenava Rizeh-Pizeh v1.0 · شنوا ریزهپیزه |
|
|
| The smallest Shenava-1 Persian ASR model: a 6.9M-parameter FastConformer distilled through the Koochik → Rizeh → Rizeh-Pizeh cascade. This repository contains the FP32 NeMo source checkpoint for evaluation, fine-tuning, and export. |
|
|
| ## ✨ At a glance | معرفی سریع |
|
|
| | | English | فارسی | |
| |---|---|---| |
| | 🐣 Role | Smallest Shenava-1 model | کوچکترین مدل خانوادهٔ Shenava-1 | |
| | 🪶 Scale | 6.9M parameters | ۶٫۹ میلیون پارامتر | |
| | 📦 Format | FP32 NeMo source | checkpoint اصلی FP32 و NeMo | |
| | 🧠 Lineage | Koochik → Rizeh → Rizeh-Pizeh | زنجیرهٔ تقطیر کوچیک ← ریزه ← ریزهپیزه | |
| | ⚡ Best for | Low-end CPUs and tiny footprint | CPU ضعیف و کمترین اندازه | |
|
|
| - Canonical repository: [`Reza2kn/Shenava-Rizeh-Pizeh-v1.0`](https://huggingface.co/Reza2kn/Shenava-Rizeh-Pizeh-v1.0) |
| - PersianML mirror: [`PersianML/Shenava-Rizeh-Pizeh-v1.0`](https://huggingface.co/PersianML/Shenava-Rizeh-Pizeh-v1.0) |
| - Teacher: [`Reza2kn/Shenava-Rizeh-v1.0`](https://huggingface.co/Reza2kn/Shenava-Rizeh-v1.0) |
|
|
| ## 🧠 Model contract |
|
|
| - Audio: mono, 16 kHz Persian speech. |
| - Encoder: `d_model=144`, 12 layers, 8x subsampling. |
| - Contexts: `[70,13]`, `[70,6]`, `[70,1]`, and `[70,0]`. |
| - Deployed head: CTC. |
| - Tokenizer: ve_tok_v4, SentencePiece BPE-1024 plus blank. |
| - Output: Persian text; use display-layer ITN when Persian digits are required. |
|
|
| The release reported real-time FP32 tract inference on a 2015 Cortex-A7 (RTF about 0.91). Treat that as a release-specific device measurement, not a universal latency guarantee. |
|
|
| ## 📊 Published evaluation |
|
|
| Decoded with context `[70,13]` and the double-benchmark ITN/Persian-digit normalization convention. |
|
|
| | Set | WER | CER | |
| |---|---:|---:| |
| | visualears-golden-6669 | 24.55% | 8.89% | |
| | FLEURS-fa | 26.95% | 10.22% | |
|
|
| ## 🚀 Load with NeMo |
|
|
| ```python |
| from nemo.collections.asr.models import ASRModel |
| |
| model = ASRModel.restore_from("shenava-rizeh-pizeh-v1.0.nemo") |
| print(model.transcribe(["speech.wav"])[0].text) |
| ``` |
|
|
| Choose this model when footprint and low-end CPU viability matter more than the accuracy available from the 32M Rizeh or 114M Koochik checkpoints. |
|
|
| ## 🇮🇷 خلاصهٔ فارسی |
|
|
| «شنوا ریزهپیزه» کوچکترین مدل خانواده است: ۶٫۹ میلیون پارامتر برای اجرای کمهزینه روی CPUهای ضعیف. این مخزن checkpoint اصلی FP32 و NeMo را نگه میدارد؛ اندازهٔ کم با افت دقت نسبت به ریزه و کوچیک همراه است. |
|
|
| ## 🌌 Explore Shenava-1 |
|
|
| [🧠 Koochik 114M](https://huggingface.co/Reza2kn/Shenava-Koochik-v1.0) · [⚖️ Rizeh 32M](https://huggingface.co/Reza2kn/Shenava-Rizeh-v1.0) · **🐣 Rizeh-Pizeh 6.9M** |
|
|
| Apache-2.0. Accuracy varies with accent, noise, overlap, recording channel, and code-switching. |
|
|
