| --- |
| language: |
| - be |
| license: apache-2.0 |
| tags: |
| - automatic-speech-recognition |
| - whisper |
| - generated_from_trainer |
| - audio |
| - speech |
| - belarusian |
| datasets: |
| - sarulab-speech/commonvoice22_sidon |
| metrics: |
| - wer |
| model-index: |
| - name: Whisper Small Belarusian Custom |
| results: |
| - task: |
| type: automatic-speech-recognition |
| name: Speech Recognition |
| dataset: |
| name: Common Voice 22 Sidon (Belarusian) |
| type: sarulab-speech/commonvoice22_sidon |
| config: be |
| split: test |
| metrics: |
| - type: wer |
| value: 27.27 |
| name: Word Error Rate |
| --- |
| |
| # Whisper Small Belarusian (Common Voice 22 Sidon) |
|
|
| A fine-tuned version of openai/whisper-small optimized for Belarusian speech recognition. This model significantly outperforms both the base Whisper Small and even the much larger Whisper Large V3 on Belarusian speech. |
|
|
| --- |
|
|
| ## Benchmark Results |
|
|
| | Model | Parameters | WER (lower is better) | |
| |:------|:----------:|----------------------:| |
| | openai/whisper-small (base) | 244M | 92.21% | |
| | openai/whisper-large-v3 | 1550M | 63.64% | |
| | **This model** | **244M** | **20.21%** | |
|
|
| **Key finding:** This fine-tuned Small model outperforms Whisper Large V3 by 36.37 percentage points, while being 6x smaller in size. |
|
|
| --- |
|
|
| ## Training Details |
|
|
| - **Base Model:** openai/whisper-small |
| - **Dataset:** sarulab-speech/commonvoice22_sidon (Belarusian subset) |
| - **Training Steps:** 1700 |
| - **Learning Rate:** 1e-5 |
| - **Batch Size:** 8 |
| - **Final Loss:** ~0.21 |
| - **Framework:** PyTorch, Transformers, Accelerate |
| |
| --- |
| |
| ## Usage |
| |
| ```python |
| from transformers import pipeline |
| |
| pipe = pipeline("automatic-speech-recognition", model="aleton/whisper-small-be-custom") |
| result = pipe("audio_file.mp3") |
| print(result["text"]) |
| ``` |
| |
| For longer audio files: |
| |
| ```python |
| result = pipe("long_audio.mp3", chunk_length_s=30, batch_size=8) |
| print(result["text"]) |
| ``` |
| |
| --- |
| |
| ## Description |
| |
| ### English |
| |
| This model demonstrates that targeted fine-tuning on language-specific data can dramatically improve performance for low-resource languages. The base Whisper models struggle with Belarusian due to limited representation in the original training data. Through fine-tuning on Common Voice 22 Sidon, this model achieves a 64.94 percentage point improvement over the base Small model and a 36.37 percentage point improvement over the Large V3 model. |
| |
| ### Русский |
| |
| Эта модель демонстрирует, что целенаправленное дообучение на языковых данных может значительно улучшить качество распознавания для малоресурсных языков. Базовые модели Whisper плохо справляются с белорусским языком из-за ограниченного представления в исходных обучающих данных. Благодаря дообучению на Common Voice 22 Sidon, эта модель показывает улучшение на 64.94 п.п. по сравнению с базовой Small моделью и на 36.37 п.п. по сравнению с Large V3. |
| |
| ### Беларуская |
| |
| Гэтая мадэль дэманструе, што мэтанакіраванае данавучанне на моўных дадзеных можа значна палепшыць якасць распазнавання для маларэсурсных моў. Базавыя мадэлі Whisper дрэнна спраўляюцца з беларускай мовай з-за абмежаванага прадстаўніцтва ў зыходных навучальных дадзеных. Дзякуючы данавучанню на Common Voice 22 Sidon, гэтая мадэль паказвае паляпшэнне на 64.94 п.п. у параўнанні з базавай Small мадэллю і на 36.37 п.п. у параўнанні з Large V3. |
| |
| --- |
| |
| ## Limitations |
| |
| - Optimized specifically for Belarusian; performance on other languages may be degraded compared to the base model |
| - Trained on Common Voice data, which may not fully represent all dialects or acoustic conditions |
| - Best results on clear audio with minimal background noise |
| |
| --- |
| |
| ## Citation |
| |
| If you use this model, please cite: |
| |
| ```bibtex |
| @misc{whisper-small-be-custom, |
| author = {aleton}, |
| title = {Whisper Small Belarusian Custom}, |
| year = {2026}, |
| publisher = {Hugging Face}, |
| url = {https://huggingface.co/aleton/whisper-small-be-custom} |
| } |
| ``` |
| |
