Instructions to use rmayormartins/speech-accent-pt-br-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rmayormartins/speech-accent-pt-br-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="rmayormartins/speech-accent-pt-br-classifier")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("rmayormartins/speech-accent-pt-br-classifier") model = AutoModelForAudioClassification.from_pretrained("rmayormartins/speech-accent-pt-br-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| license: ecl-2.0 | |
| datasets: | |
| - mozilla-foundation/common_voice_11_0 | |
| language: | |
| - en | |
| - pt | |
| metrics: | |
| - accuracy | |
| library_name: transformers | |
| tags: | |
| - code | |
| # Speech Portuguese (Brazilian) Accent Classifier | |
| 🎙️🤖🇧🇷 | |
| This project is a speech accent classifier that distinguishes between Portuguese (Brazilian) and other accents. | |
| ## Project Overview | |
| This application uses a trained model to classify speech accents into two categories: | |
| 1. Portuguese (Brazilian) | |
| 2. Other | |
| The model is based on the author's work [results] and utilizes the Portuguese portion of the Common Voice dataset (version 11.0) from Mozilla Foundation. | |
| ## Dataset | |
| The project uses the Portuguese subset of the Common Voice dataset: | |
| - Dataset: "mozilla-foundation/common_voice_11_0", "pt" | |
| Brazilian accents included in the dataset: | |
| - Português do Brasil, Região Sul do Brasil | |
| - Paulistano | |
| - Paulista, Brasileiro | |
| - Carioca | |
| - Mato Grosso | |
| - Mineiro | |
| - Interior Paulista | |
| - Gaúcho | |
| - Nordestino | |
| - And various regional mixes | |
| ## Model and Processor | |
| The project utilizes the following model and processor: | |
| - Base Model: "facebook/wav2vec2-base-960h" | |
| - Processor: Wav2Vec2Processor.from_pretrained | |
| ## Model Versions | |
| Was trained three versions of the model with different configurations: | |
| 1. **(OLD) v 1.1**: | |
| - Epochs: 3 | |
| - Training samples: 1000 | |
| - Validation samples: 200 | |
| 2. **(OLD) v 1.2**: | |
| - Epochs: 10 | |
| - Training samples: 1000 | |
| - Validation samples: 500 | |
| 3. **(NEW) v 1.3**: | |
| - Epochs: 20 | |
| - Training samples: 5000 | |
| - Validation samples: 1000 | |
| All models were trained using high RAM GPU on Google Colab Pro. | |
| ## Model Structure (files) | |
| Each version of the model includes the following files: | |
| results config.json | preprocessor_config.json | model.safetensors | special_tokens_map.json | tokenizer_config.json | vocab.json | |
| ## How to Use | |
| Test with recording or uploading an audio file. To test, I recommend short sentences. | |
| ## License | |
| This project is licensed under the Eclipse Public License 2.0 (ECL-2.0). | |
| ## Developer Information | |
| Developed by Ramon Mayor Martins (2024) | |
| - Email: rmayormartins@gmail.com | |
| - Homepage: https://rmayormartins.github.io/ | |
| - Twitter: @rmayormartins | |
| - GitHub: https://github.com/rmayormartins | |
| ## Acknowledgements | |
| Special thanks to Instituto Federal de Santa Catarina (Federal Institute of Santa Catarina) IFSC-São José-Brazil. | |
| ## Contact | |
| For any queries or suggestions, please contact the developer using the information provided above. |