Automatic Speech Recognition
NeMo
Persian
speech
persian
farsi
fastconformer
ctc
streaming
on-device
shenava
shenava-1
visualears
rnnt
distillation
Instructions to use Reza2kn/Shenava-Rizeh-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use Reza2kn/Shenava-Rizeh-v1.0 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("Reza2kn/Shenava-Rizeh-v1.0") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
| language: | |
| - fa | |
| license: cc-by-nc-4.0 | |
| library_name: nemo | |
| pipeline_tag: automatic-speech-recognition | |
| base_model: | |
| - Reza2kn/Shenava-Koochik-v1.0 | |
| base_model_relation: finetune | |
| tags: | |
| - automatic-speech-recognition | |
| - speech | |
| - persian | |
| - farsi | |
| - fastconformer | |
| - ctc | |
| - streaming | |
| - on-device | |
| - shenava | |
| - shenava-1 | |
| - visualears | |
| - rnnt | |
| - nemo | |
| - distillation | |
| metrics: | |
| - wer | |
| - cer | |
| datasets: | |
| - Reza2kn/visualears-persian-asr-16k | |
| - Reza2kn/visualears-golden-6669 | |
| - Reza2kn/fleurs-fa-benchmark | |
| # Shenava — Rizeh v1.0 (32M) · Persian streaming ASR | |
| **Rizeh** (ریزه, “tiny”) is the 32M mid‑tier of the **Shenava‑1** family — a FastConformer Hybrid RNNT/CTC model distilled (logit + feature KD) from the [Koochik v1.0 114M teacher](https://huggingface.co/Reza2kn/Shenava-Koochik-v1.0). CTC head deployed. fp32 NeMo source; quants in own repos below. | |
| ## The Shenava‑1 family | |
| A knowledge‑distillation cascade of on‑device Persian ASR models — one teacher distilled down to a 6.9M student. This model is one member; its siblings: | |
| - [`Reza2kn/Shenava-Koochik-v1.0`](https://huggingface.co/Reza2kn/Shenava-Koochik-v1.0) — **Koochik v1.0** (114M) · teacher / flagship — on-device WER record | |
| - [`Reza2kn/Shenava-Rizeh-v1.0`](https://huggingface.co/Reza2kn/Shenava-Rizeh-v1.0) — **Rizeh v1.0** (32M) · mid-tier student ◀ **this model (or its parent)** | |
| - [`Reza2kn/Shenava-Rizeh-Pizeh-v1.0`](https://huggingface.co/Reza2kn/Shenava-Rizeh-Pizeh-v1.0) — **Rizeh Pizeh v1.0** (6.9M) · tiniest — real-time on a 2015 Cortex-A7 | |
| ## Benchmark — fair WER/CER | |
| ITN + Persian‑digit normalizer (the [double‑benchmark](https://huggingface.co/spaces/Reza2kn/persian-asr-double-benchmark) convention), decoded @ `att_context_size=[70,13]`. | |
| | Member | golden‑6669 WER | CER | FLEURS‑fa WER | CER | | |
| |---|---|---|---|---| | |
| | Koochik v1.0 (114M) | **7.49%** | 2.30% | **10.64%** | 3.79% | | |
| | Rizeh v1.0 (32M) | 12.11% | 3.94% | 14.45% | 5.10% | | |
| | Rizeh Pizeh v1.0 (6.9M) | 24.55% | 8.89% | 26.95% | 10.22% | | |
| Koochik v1.0 is **#2 on the public double‑benchmark, behind only cloud Gemini** — the best on‑device Persian ASR, beating a 1.5B Whisper‑Persian by >2× WER at 1/13 the size. | |
| ## Quantized formats (own repos) | |
| - [`Shenava-Rizeh-v1.0-ONNX-fp16`](https://huggingface.co/Reza2kn/Shenava-Rizeh-v1.0-ONNX-fp16) | |
| - [`Shenava-Rizeh-v1.0-CoreML-fp16`](https://huggingface.co/Reza2kn/Shenava-Rizeh-v1.0-CoreML-fp16) | |
| 32M, d_model 256 / 16 layers, ×8 subsampling, multi‑latency `[[70,13],[70,6],[70,1],[70,0]]`. | |
| Tokenizer: ve_tok_v4 (SentencePiece BPE‑1024 +blank, digit/punct/«»‑aware). Numbers are **spoken‑form**; apply ITN at display for digits. Part of [VisualEars / Shenava](https://shenava.app). | |