AreejB/wav2vec2-xlsr-english-speech-emotion-recognition

Emotion Recognition in English Using RAVDESS and Wav2Vec 2.0

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This model extracts emotions from audio recordings. It was trained on RAVDESS, a dataset containing English audio recordings. The model recognises six emotions: anger, disgust, fear, happiness, sadness and surprise.

The model recreates the work of this Greek emotion extractor using a pre-trained Wav2Vec2 model to process the data.

Model Details

Model Description

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• —Adapted from: Emotion Recognition in Greek
• —Model type: NN with CTC
• —Language(s) (NLP): English
• —Finetuned from model: wav2vec2

How to Get Started with the Model

Use the code below to get started with the model.

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Training Details

Training Data

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The RAVDESS dataset was split into training, validation and test sets with 60, 20 and 20 splits, respectively.

Training Procedure

The fine-tuning process was centred on four hyper-parameters:

• —the number of batches (4, 8),
• —gradient accumulation steps (GAS) (2, 4, 6, 8),
• —number of epochs (10, 20) and
• —the learning rate (1e-3, 1e-4, 1e-5).

Each experiment was repeated 10 times.

Evaluation

The set of hyper-parameters resulting in the best performance is: 4 batches, 4 GAS, 10 epochs and 1e-4 learning rate

Testing

The model was retrained on the combined train and validation sets using the best hyper-parameter set. The performance on the test set has an average Accuracy and F1 scores of 84.84% (SD 2 and 2.08, respectively)

Results

We retained the model providing the highest performance over the 10 runs.

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