Emotion cause extraction in conversations (ECEC) is an important task in emotion analysis, aiming to extract the text spans, i.e., parts in utterances, that reflect the causes of a certain type of emotion embedded in a target utterance in the conversation history. Since conversations are ...
(Emotion Cause Extraction in Dialogues, ECED). The setting of the two tasks requires first ERD and then ECED, ignoring the mutual complement between emotion and cause. To fix this, some new tasks are proposed to extract them simultaneously. Although the current research on these tasks has ...
/blue_score: A folder that contains the scripts for BLEU score computation for emotion-cause extraction. /cluster: A folder that contains the scripts for generating clusters for the case study. /Emotion_Classification: A folder that contains scripts for training and testing emotion classification usi...
Hua Y, Huang Y, Huang S, et al (2024) Causal discovery inspired unsupervised domain adaptation for emotion-cause pair extraction. arXiv preprint arXiv:2406.15490 Hu J, Liu Y, Zhao J, et al (2021b) MMGCN: Multimodal fusion via deep graph convolution network for emotion recognition in conver...
Next, the sample input text or an entire text corpus is received by Module 3. This input is pushed through the embedding generator and then projected on to the emotional embedding space. Thennearest neighbour extraction process identifies the closest emotion terms based on this projection. This pr...
(e.g., classification, summarization, question answering, and information extraction) have been facilitated by the advent of deep learning (DL) methods, which are able to extract higher-level and more complex feature representations through multiple processing layers, compared to conventional machine ...
[62]. Researchers have also utilized cues like formants, Mel frequency cepstral coefficients, pause, teager energy operated-based features, log frequency power coefficients, and linear prediction cepstral coefficients for feature extraction. With the advent of deep learning, new opportunities have arisen...
Figure 1. Overview of the proposed framework for emotion-aware response generation in LLMs. The Psychotherapy Transcripts Dataset is processed through text extraction and splitting, generating word-level, sentence-level, and session-level embeddings. These embeddings are enriched with external emotional ...
Emotion detection in psychological texts by fine-tuning BERT using emotion–cause pair extraction. Int. J. Speech Technol. 2022, 25, 727–743. [CrossRef] 15. Xu, X.; Yao, B.; Dong, Y.; Gabriel, S.; Yu, H.; Hendler, J.; Ghassemi, M.; Dey, A.K.; Wang, D. Mental-LLM: ...
Figure 1. Overview of the proposed framework for emotion-aware response generation in LLMs. The Psychotherapy Transcripts Dataset is processed through text extraction and splitting, generating word-level, sentence-level, and session-level embeddings. These embeddings are enriched with external emotional ...