Emotion Carrier Recognition from Personal Narratives
- URL: http://arxiv.org/abs/2008.07481v2
- Date: Thu, 24 Jun 2021 15:24:53 GMT
- Title: Emotion Carrier Recognition from Personal Narratives
- Authors: Aniruddha Tammewar, Alessandra Cervone, Giuseppe Riccardi
- Abstract summary: Personal Narratives (PNs) are recollections of facts, events, and thoughts from one's own experience.
We propose a novel task for Narrative Understanding: Emotion Carrier Recognition (ECR)
- Score: 74.24768079275222
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Personal Narratives (PN) - recollections of facts, events, and thoughts from
one's own experience - are often used in everyday conversations. So far, PNs
have mainly been explored for tasks such as valence prediction or emotion
classification (e.g. happy, sad). However, these tasks might overlook more
fine-grained information that could prove to be relevant for understanding PNs.
In this work, we propose a novel task for Narrative Understanding: Emotion
Carrier Recognition (ECR). Emotion carriers, the text fragments that carry the
emotions of the narrator (e.g. loss of a grandpa, high school reunion), provide
a fine-grained description of the emotion state. We explore the task of ECR in
a corpus of PNs manually annotated with emotion carriers and investigate
different machine learning models for the task. We propose evaluation
strategies for ECR including metrics that can be appropriate for different
tasks.
Related papers
- Think out Loud: Emotion Deducing Explanation in Dialogues [57.90554323226896]
We propose a new task "Emotion Deducing Explanation in Dialogues" (EDEN)
EDEN recognizes emotion and causes in an explicitly thinking way.
It can help Large Language Models (LLMs) achieve better recognition of emotions and causes.
arXiv Detail & Related papers (2024-06-07T08:58:29Z) - ECR-Chain: Advancing Generative Language Models to Better Emotion-Cause Reasoners through Reasoning Chains [61.50113532215864]
Causal Emotion Entailment (CEE) aims to identify the causal utterances in a conversation that stimulate the emotions expressed in a target utterance.
Current works in CEE mainly focus on modeling semantic and emotional interactions in conversations.
We introduce a step-by-step reasoning method, Emotion-Cause Reasoning Chain (ECR-Chain), to infer the stimulus from the target emotional expressions in conversations.
arXiv Detail & Related papers (2024-05-17T15:45:08Z) - Language Models (Mostly) Do Not Consider Emotion Triggers When Predicting Emotion [87.18073195745914]
We investigate how well human-annotated emotion triggers correlate with features deemed salient in their prediction of emotions.
Using EmoTrigger, we evaluate the ability of large language models to identify emotion triggers.
Our analysis reveals that emotion triggers are largely not considered salient features for emotion prediction models, instead there is intricate interplay between various features and the task of emotion detection.
arXiv Detail & Related papers (2023-11-16T06:20:13Z) - Automatic Emotion Experiencer Recognition [12.447379545167642]
We show that experiencer detection in text is a challenging task, with a precision of.82 and a recall of.56 (F1 =.66)
We show that experiencer detection in text is a challenging task, with a precision of.82 and a recall of.56 (F1 =.66)
arXiv Detail & Related papers (2023-05-26T08:33:28Z) - Experiencer-Specific Emotion and Appraisal Prediction [13.324006587838523]
Emotion classification in NLP assigns emotions to texts, such as sentences or paragraphs.
We focus on the experiencers of events, and assign an emotion (if any holds) to each of them.
Our experiencer-aware models of emotions and appraisals outperform the experiencer-agnostic baselines.
arXiv Detail & Related papers (2022-10-21T16:04:27Z) - x-enVENT: A Corpus of Event Descriptions with Experiencer-specific
Emotion and Appraisal Annotations [13.324006587838523]
We argue that a classification setup for emotion analysis should be performed in an integrated manner, including the different semantic roles that participate in an emotion episode.
Based on appraisal theories in psychology, we compile an English corpus of written event descriptions.
The descriptions depict emotion-eliciting circumstances, and they contain mentions of people who responded emotionally.
arXiv Detail & Related papers (2022-03-21T12:02:06Z) - Detecting Emotion Carriers by Combining Acoustic and Lexical
Representations [7.225325393598648]
We focus on Emotion Carriers (EC) defined as the segments that best explain the emotional state of the narrator.
EC can provide a richer representation of the user state to improve natural language understanding.
We leverage word-based acoustic and textual embeddings as well as early and late fusion techniques for the detection of ECs in spoken narratives.
arXiv Detail & Related papers (2021-12-13T12:39:53Z) - Emotion Recognition From Gait Analyses: Current Research and Future
Directions [48.93172413752614]
gait conveys information about the walker's emotion.
The mapping between various emotions and gait patterns provides a new source for automated emotion recognition.
gait is remotely observable, more difficult to imitate, and requires less cooperation from the subject.
arXiv Detail & Related papers (2020-03-13T08:22:33Z) - Annotation of Emotion Carriers in Personal Narratives [69.07034604580214]
We are interested in the problem of understanding personal narratives (PN) - spoken or written - recollections of facts, events, and thoughts.
In PN, emotion carriers are the speech or text segments that best explain the emotional state of the user.
This work proposes and evaluates an annotation model for identifying emotion carriers in spoken personal narratives.
arXiv Detail & Related papers (2020-02-27T15:42:39Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.