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Ethio-ASR is a suite of multilingual Automatic Speech Recognition (ASR) models that support five Ethiopian languages: Amharic, Tigrinya, Afaan Oromo, Sidama, and Wolaytta. The ASR model in this repo is based on the wav2vec2‑bert-2.0 pre-trained model by fine-tuning it on the WAXAL Speech Dataset. - **Developed by:** Ethio-ASR Team - **Task:** Speech Recognition (ASR) and Language Identification (LID) - **Languages:** Amharic, Tigrinya, Afaan Oromo, Sidama, and Wolaytta - **License:** CC-BY-4.0 - **Finetuned from:** facebook/w2v-bert-2.0 *📌 ASR model in this HF repo* | Model | # Params | Amharic | Tigrinya | Oromo | Wolaytta | Sidaama | Avg. | |------|----------|----------|-----------|--------|-----------|----------|------| | Ethio-ASR (afrihubert) | 92M | 30.95 | 42.42 | 27.57 | 40.44 | 34.02 | 35.08 | | Ethio-ASR (mms-300) | 300M | 30.19 | 41.62 | 26.41 | 39.10 | 32.66 | 33.99 | | Ethio-ASR (mms-1b) | 1B | 26.14 | 37.63 | **23.69** | **37.51** | **31.02** | 31.20 | | **Ethio-ASR (w2v-bert-2.0)** 📌 | 600M | **22.92** | **35.22** | 24.44 | 38.19 | 31.65 | **30.48** |

Speech recognition
Input Audio→ Output Text
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This model is a fine-tuned version of Wav2Vec2-BERT 2.0 for Kinyarwanda automatic speech recognition (ASR). It was trained on the 1000 hours dataset from the Kinyarwanda ASR hackthon on Kaggle (Track B), dataset covering Health, Government, Finance, Education, and Agriculture domains. The model is robust and the in-domain WER is below 8.4%. - **Developed by:** Badr al-Absi - **Model type:** Speech Recognition (ASR) - **Language:** Kinyarwanda (rw) - **License:** CC-BY-4.0 - **Finetuned from:** facebook/w2v-bert-2.0 - **Repository:** https://huggingface.co/badrex/w2v-bert-2.0-kinyarwanda-asr - **Dataset:** Kinyarwanda ASR Track B

Speech recognition
Input Audio→ Output Text
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View details ↗
Source / docs ↗
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