[Jan. 2024] emotion2vec has been integrated into modelscope and FunASR. [Dec. 2023] We release the paper, and create a WeChat group for emotion2vec. [Nov. 2023] We release code, checkpoints, and extracted features for emotion2vec.Model CardGitHub Repo: emotion2vecModel...
The paper will propose Academics Emotion Analysis Model that will analyse the sentiments of academics whether they agree to use ChatGPT in writing articles or not. Word2vec and Term Frequency Inverse Document Frequency (TFIDF) and word2vec feature selection methods will be used and three machine...
In this paper, we propose WavFusion, a multimodal speech emotion recognition framework that addresses critical research problems in effective multimodal fusion, heterogeneity among modalities, and discriminative representation learning. By leveraging a gated cross-modal attention mechanism and multimodal ...
Speech emotion recognition poses challenges due to the varied expression of emotions through intonation and speech rate. In order to reduce the loss of emotional information during the recognition process and to enhance the extraction and classification of speech emotions and thus improve the ability of...
This paper introduces a deep learning constructed emotional recognition model for Arabic speech dialogues. The developed model employs the state of the art audio representations include wav2vec2.0 and HuBERT. The experiment and performance results of our model overcome the previous known outcomes. 展开...
Finally, Section 5 provides a discussion, and Section 6 concludes the paper. 2. Emotion Embedding Extraction In this section, we will introduce how to extract emotion embedding by fine-tuning the pre-trained W2V2 model with the training data and corresponding label information. Next, we first ...