AntEngage Empathy Conversation Dataset

Published: 7 August 2026| Version 1 | DOI: 10.17632/c7d2mcp99w.1
Contributor:
Dibyaprakash Pradhan

Description

AntEngage Empathy Conversation Dataset (Version 1.0.0) is an open-access dataset containing 4,008 AI-synthesized multi-turn empathy-focused conversations designed for research and development in natural language processing, conversational AI, and affective computing. The dataset was created by AntEngage Technology Private Limited as part of the AntEngage Language Model (AELM) initiative. Each conversation represents realistic emotional support interactions involving situations such as caregiver burnout, grief, loneliness, workplace stress, parenting challenges, and emotional exhaustion. Dialogues were generated using a structured synthetic data generation pipeline followed by automated quality verification to improve diversity, coherence, naturalness, and safety. No conversations were collected from real individuals. The dataset contains no personally identifiable information (PII) and consists entirely of AI-generated content intended for research and model development. The primary objective of this dataset is to support the development and evaluation of empathetic dialogue systems, conversational agents, instruction tuning datasets, and language models capable of producing supportive and emotionally appropriate responses. Dataset Characteristics • 4,008 conversations • 79,616 dialogue turns • English language • Multi-turn dialogue format • JSONL and CSV formats • License: Creative Commons Attribution 4.0 International (CC BY 4.0) Potential Applications • Empathetic dialogue generation • Conversational AI research • Instruction tuning for large language models • Affective computing • Mental health NLP research • Dialogue system benchmarking • Human-AI interaction research This dataset is intended solely for research and educational purposes. Although the conversations model supportive communication, they are not a substitute for professional medical or mental health advice.

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Categories

English, Mental Health, Natural Language Processing, Affective Computing, Emotional Intelligence, Empathy, Conversational Agent, Meta Dataset, Large Language Model

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