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This project was developed for my senior thesis at Princeton University. Paper being published soon.
Model source
Source description
This project was developed for my senior thesis at Princeton University. Paper being published soon.
TuBERT is a multimodal speech emotion recognition model that runs in real-time and on-device. I designed it with PNGTubers in mind, but there are plenty of other applications for it as well!
To test the model for yourself using a GUI, see the GitHub repository for installation instructions.
Sources
1 sourceVerified Aug 29
Model artifacts
2 artifactsSource excerpts
2 excerpts--- license: mit language: - en metrics: - accuracy - f1 - precision base_model: - bhadresh-savani/distilbert-base-uncased-emotion pipeline_tag: audio-classification tags: - speech - emotion - ser - classification --- # TuBERT: Multimodal Speech Emotion Recognition For Real-Time Avatar Control *This project was developed for my senior thesis at Princeton University. Paper being published soon.* ## About TuBERT is a multimodal speech emotion recognition model that runs in real-time and on-device. I designed it with PNGTubers in mind, but there are plenty of other applications for it as well! To test the model for yourself using a GUI, see the [GitHub repository](https://github.com/YacoubKahkajian/TuBERT) for installation instructions. ## Usage `tubert.pt` is the base TuBERT model trained on MELD, described in the paper and used by default for evaluation. `tubert_iemocap.pt` is the version of the model fine-tuned on IEMOCAP.
tubert.pt is the base TuBERT model trained on MELD, described in the paper and used by default for evaluation. tubert_iemocap.pt is the version of the model fine-tuned on IEMOCAP.
Source context: 0 downloads · 0 likes · Pipeline audio-classification · Repo yacoubk/TuBERT
