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[ACL 2024] Official PyTorch code for extracting features and training downstream models with emotion2vec: Self-Supervised Pre-Training for Speech Emotion Representation

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Hello, I am curious about the fine-tuning dataset for emotion2vec+ base. Can I assume that the fine-tuning was done using the downstream tasks datasets mentioned in 'Table 1: The datasets...

According to the official description, the motion2vec_plus model should be able to categorize speech into 9 classes, but why did I actually run it with only 5 classes(angry、happy、neutral、sad and )?...

Traceback (most recent call last): File "/mnt/XXL/emotion2vec-large/scripts/extract_features.py", line 70, in main() File "/mnt/XXL/emotion2vec-large/scripts/extract_features.py", line 39, in main model, cfg, task = fairseq.checkpoint_utils.load_model_ensemble_and_task([checkpoint_dir]) File "/mnt/XXL/env/emotion2vec/lib/python3.9/site-packages/fairseq/checkpoint_utils.py", line 436, in load_model_ensemble_and_task task =...