Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
97 tokens/sec
GPT-4o
53 tokens/sec
Gemini 2.5 Pro Pro
44 tokens/sec
o3 Pro
5 tokens/sec
GPT-4.1 Pro
47 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

AdCOFE: Advanced Contextual Feature Extraction in Conversations for emotion classification (2104.04517v1)

Published 9 Apr 2021 in cs.CL and cs.LG

Abstract: Emotion recognition in conversations is an important step in various virtual chat bots which require opinion-based feedback, like in social media threads, online support and many more applications. Current Emotion recognition in conversations models face issues like (a) loss of contextual information in between two dialogues of a conversation, (b) failure to give appropriate importance to significant tokens in each utterance and (c) inability to pass on the emotional information from previous utterances.The proposed model of Advanced Contextual Feature Extraction (AdCOFE) addresses these issues by performing unique feature extraction using knowledge graphs, sentiment lexicons and phrases of natural language at all levels (word and position embedding) of the utterances. Experiments on the Emotion recognition in conversations dataset show that AdCOFE is beneficial in capturing emotions in conversations.

User Edit Pencil Streamline Icon: https://streamlinehq.com
Authors (5)
  1. Vaibhav Bhat (1 paper)
  2. Anita Yadav (8 papers)
  3. Sonal Yadav (1 paper)
  4. Dhivya Chandrasekaran (6 papers)
  5. Vijay Mago (24 papers)
Citations (4)

Summary

We haven't generated a summary for this paper yet.