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End-to-end Transfer Learning for Speaker-independent Cross-language Speech Emotion Recognition
We use the wav2vec 2. 0 pre-trained model to transform audio time-domain waveforms from different languages, different speakers and different recording conditions into a feature space shared by multiple languages, thereby it reduces the language variabilities in the speech features.
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