相关论文: EmoG- Towards Emojifying Gmail Conversations
With the advent of generative AI and large language models, embodied conversational agents are becoming synonymous with online interactions. These agents possess vast amounts of knowledge but suffer from exhibiting limited emotional…
In this paper, we propose Emo2Vec which encodes emotional semantics into vectors. We train Emo2Vec by multi-task learning six different emotion-related tasks, including emotion/sentiment analysis, sarcasm classification, stress detection,…
A humanized dialogue system is expected to generate empathetic replies, which should be sensitive to the users' expressed emotion. The task of empathetic dialogue generation is proposed to address this problem. The essential challenges lie…
Textual sentiment analysis and emotion detection consists in retrieving the sentiment or emotion carried by a text or document. This task can be useful in many domains: opinion mining, prediction, feedbacks, etc. However, building a general…
In the burgeoning realm of cryptocurrency, social media platforms like Twitter have become pivotal in influencing market trends and investor sentiments. In our study, we leverage GPT-4 and a fine-tuned transformer-based BERT model for a…
When a Commit Message Generation (CMG) system is integrated into the IDEs and other products at JetBrains, we perform online evaluation based on user acceptance of the generated messages. However, performing online experiments with every…
Software developers are increasingly using machine learning APIs to implement 'intelligent' features. Studies show that incorporating machine learning into an application increases technical debt, creates data dependencies, and introduces…
Emotion has a significant influence on how one thinks and interacts with others. It serves as a link between how a person feels and the actions one takes, or it could be said that it influences one's life decisions on occasion. Since the…
Quantitative research of emotions in psychology and machine-learning methods for extracting emotion components from text messages open an avenue for physical science to explore the nature of stochastic processes in which emotions play a…
Movie story analysis requires understanding characters' emotions and mental states. Towards this goal, we formulate emotion understanding as predicting a diverse and multi-label set of emotions at the level of a movie scene and for each…
Explainable Multimodal Emotion Recognition (EMER) is an emerging task that aims to achieve reliable and accurate emotion recognition. However, due to the high annotation cost, the existing dataset (denoted as EMER-Fine) is small, making it…
This work explores the utility of implicit behavioral cues, namely, Electroencephalogram (EEG) signals and eye movements for gender recognition (GR) and emotion recognition (ER) from psychophysical behavior. Specifically, the examined cues…
Emotionally annotated databases are repositories of multimedia documents with annotated affective content that elicit emotional responses in exposed human subjects. They are primarily used in research of human emotions, attention and…
This paper describes our system that has been submitted to SemEval-2018 Task 1: Affect in Tweets (AIT) to solve five subtasks. We focus on modeling both sentence and word level representations of emotion inside texts through large distantly…
Consumers are used to consulting posted reviews on the Internet before buying a product. But it's difficult to know the global opinion considering the important number of those reviews. Sentiment analysis afford detecting polarity…
Emotional Image Content Generation (EICG) aims to generate semantically clear and emotionally faithful images based on given emotion categories, with broad application prospects. While recent text-to-image diffusion models excel at…
Voice messages, by nature, prevent users from gauging the emotional tone without fully diving into the audio content. This hinders the shared emotional experience at the pre-retrieval stage. Research scarcely explored "Emotional…
Sentiment analysis is a well-known natural language processing task that involves identifying the emotional tone or polarity of a given piece of text. With the growth of social media and other online platforms, sentiment analysis has become…
Speech emotions play a crucial role in human-computer interaction, shaping engagement and context-aware communication. Despite recent advances in spoken dialogue systems, a holistic system for evaluating emotional reasoning is still…
Social Networks allow users to self-present by sharing personal contents with others which may add comments. Recent studies highlighted how the emotions expressed in a post affect others' posts, eliciting a congruent emotion. So far, no…