---
language:
  - ur
  - sd
license: apache-2.0
pretty_name: Canopy-M
pipeline_tag: automatic-speech-recognition
library_name: pytorch
tags:
  - automatic-speech-recognition
  - speech
  - ctc
  - conformer
  - urdu
  - sindhi
---

# Canopy-M

<div align="center">
  <img src="figures/canopy-m-logo.png" alt="Canopy-M Logo" width="220"/>
</div>

Canopy-M is a 57.9-million-parameter Conformer-CTC model for Urdu and Sindhi. It is non-autoregressive: a Macaron encoder predicts a token at every frame, and greedy CTC reads that sequence.


![Canopy-M versus Whisper on the Urdu and Sindhi development sets](figures/overview_cer_wer.png)

## Use

Install the library once, then point it at any published variant:

```bash
pip install torch torchaudio soundfile
pip install git+https://github.com/Proxima-AI-Co/canopy.git
hf auth login
canopy-transcribe clip.wav --model canopy-m --language urd
canopy-transcribe clip.wav --model ProximaAI/Canopy-M --language snd --device cpu
```

```python
from canopy import Canopy

asr = Canopy.from_pretrained("canopy-m")
print(asr.transcribe("clip.wav", language="urd"))
print(asr.transcribe("clip.wav", language="snd"))
```


## Training data

About **186.7 hours** were used in training.

| Language | Source | Train hours | Dev hours | Labels |
|---|---|---:|---:|---|
| Urdu | Common Voice + mahwiz + UrduSpeech | ~79.6 | ~17 | human |
| Sindhi | Common Voice | 71.5 | 0.10 | human; mostly unvalidated `other` |
| Sindhi | FLEURS `sd_in` | 12.3 | 1.33 | human, CC-BY-4.0 |


## Intended use

Research transcription of read Urdu and Sindhi at 16 kHz, one language per utterance, with the language given.

## Limitations

- Sindhi Common Voice development audio is 0.10 hours (70 utterances). Most of the Sindhi score is FLEURS.
- Common Voice Sindhi training audio is mostly unvalidated `other`, included with `--include-unvalidated`.
- Urdu Common Voice CER is 0.248. The headline 0.132 is pulled down by UrduSpeech and mahwiz.
- A wrong language id can cross Urdu and Sindhi, which share a Perso-Arabic script.
- No word n-gram was used in this table. Fusion can still overwrite a correct acoustic hypothesis.

## Citation

```bibtex
@software{canopy_m_2026,
  title = {Canopy-M: Conformer-CTC speech recognition for Urdu and Sindhi},
  author = {{Proxima AI}},
  year = {2026},
  url = {https://huggingface.co/ProximaAI/Canopy-M},
  license = {Apache-2.0}
}
```

Also cite Common Voice, and FLEURS.