---
library_name: transformers
license: cc-by-4.0
datasets:
- badrex/ethiopian-speech-flat
language:
- ti
metrics:
- wer
---

<div align="center" style="line-height: 1;">
  <h1>Automatic Speech Recognition for Tigrinya </h1>
  <a href="https://huggingface.co/datasets/badrex/ethiopian-speech-flat" target="_blank" style="margin: 2px;">
    <img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Dataset-ffc107?color=ffca28&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
  <a href="https://huggingface.co/spaces/badrex/Ethiopia-ASR" target="_blank" style="margin: 2px;">
    <img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Space-ffc107?color=c62828&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
  <a href="https://creativecommons.org/licenses/by/4.0/deed.en" style="margin: 2px;">
    <img alt="License" src="https://img.shields.io/badge/License-CC%20BY%204.0-lightgrey.svg" style="display: inline-block; vertical-align: middle;"/>
  </a>
</div>



## 🍇 Model Description 

This is a Automatic Speech Recognition (ASR) model for Tigrinya, an Afroasiatic language that is primarily spoken by the Tigrinya and Tigrayan peoples, native to Eritrea and to the Tigray Region of Ethiopia. 
It is fine‑tuned from Wav2Vec2‑BERT 2.0 using the [Ethio speech corpus](https://huggingface.co/datasets/badrex/ethiopian-speech-flat).

- **Developed by:** Badr al-Absi
- **Model type:** Speech Recognition (ASR)
- **Languages:** Tigrinya
- **License:** CC-BY-4.0
- **Finetuned from:** facebook/w2v-bert-2.0

## 🎧 Direct Use

``` python
from transformers import Wav2Vec2BertProcessor, Wav2Vec2BertForCTC
import torchaudio, torch

processor = Wav2Vec2BertProcessor.from_pretrained("badrex/w2v-bert-2.0-tigrinya-asr")
model = Wav2Vec2BertForCTC.from_pretrained("badrex/w2v-bert-2.0-tigrinya-asr")

audio, sr = torchaudio.load("audio.wav")
inputs = processor(audio.squeeze(), sampling_rate=sr, return_tensors="pt")

with torch.no_grad():
    logits = model(**inputs).logits

pred_ids = torch.argmax(logits, dim=-1)
transcription = processor.batch_decode(pred_ids)[0]

print(transcription)
```

## 🔧 Downstream Use

-   Voice assistants
-   Accessibility tools
-   Research baselines

## 🚫 Out‑of‑Scope Use

-   Other languages besides Tigrinya
-   High‑stakes deployments without human review
-   Noisy audio without further tuning

## ⚠️ Risks & Limitations

Performance varies with accents, dialects, and recording quality.



## 📌 Citation

``` bibtex
@misc{w2v_bert_ethiopian_asr,
  author = {Badr M. Abdullah},
  title = {Fine-tuning Wav2Vec2-BERT 2.0 for Ethiopian ASR},
  year = {2025},
  url = {https://huggingface.co/badrex/w2v-bert-2.0-tigrinya-asr}
}
```