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Yujun Feng

dblp:20/8548 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
—ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Question answering and dialogue systems · 62% Information extraction and text analysis · 19% Speech recognition and synthesis · 19%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Question answering and dialogue systems
multimodal dialogue system
0.912025
A Multimodal AI Dialogue System for Unified Document, Visual, and Audio Interaction · IJCAI 2025
Natural language and speech › Information extraction and text analysis
document analysis
0.312025
A Multimodal AI Dialogue System for Unified Document, Visual, and Audio Interaction · IJCAI 2025
Natural language and speech › Speech recognition and synthesis
speech interaction
0.312025
A Multimodal AI Dialogue System for Unified Document, Visual, and Audio Interaction · IJCAI 2025

Methods — techniques the papers use, named apart from their topics

speech processing · 0.9multimodal input pipeline · 0.9
YearPublicationVenuePosition
2025 A Multimodal AI Dialogue System for Unified Document, Visual, and Audio Interaction
abstract
This paper presents a multimodal intelligent dialogue system that seamlessly integrates document analysis, visual media processing, and audio interaction within a unified web interface. The system ensures secure user identity verification through persistent conversational management, leveraging textual document analysis, dynamic context integration, and cross-media interactions via video, image, and real-time speech processing. Our approach introduces three key innovations: (1) context-aware document analysis through text extraction, (2) a multimodal input pipeline supporting images, videos, and audio, and (3) persistent chat history management for maintaining conversational continuity. The system facilitates seamless transitions between audio and text, enabling natural interactions by processing audio input and converting text responses into speech. Additionally, the platform provides an intuitive interface for document uploads, camera capture, and audio recording, while ensuring conversation context is preserved across sessions. This implementation demonstrates the practical integration of multimodal input in an interactive artificial intelligence (AI) system, showcasing its potential for enhanced user engagement and interaction.
Yujun Feng
IJCAI1