# High-precision Emotion Recognition

Emotion dominance analysis model fine-tuned based on RobBERT-v2 Dutch foundation model

A German emotion classification model fine-tuned based on RoBERTa, capable of classifying text into six emotion categories: anger, fear, disgust, sadness, happiness, and none of the above.

A fine-tuned Arabic speech emotion recognition model based on facebook/wav2vec2-base, achieving 99.92% accuracy on the evaluation dataset.

This model is fine-tuned from Google's T5-base model on an emotion recognition dataset, designed for text sentiment classification tasks, capable of classifying text into 6 basic emotions.