Yan Ke

Carnegie Mellon University

Papers

1

Total Citations

45

H-Index

1

About

Yan Ke is a pioneering researcher in audio and multimedia information retrieval, best known for advancing the field of sound object localization and retrieval in complex environments. Their seminal work, "SOLAR: Sound Object Localization and Retrieval in Complex Audio Environments" (2006), with 45 citations, introduced a groundbreaking system capable of identifying and locating specific sound objects—such as dog barks or car horns—amidst noisy, real-world audio. This contribution addressed a critical gap in multimedia retrieval, security, and mobile robotics, where prior research had largely overlooked the challenges of isolating sounds in cluttered acoustic scenes. Ke’s work demonstrated how to combine signal processing and machine learning techniques to enable machines to "hear" and pinpoint sounds with high accuracy, laying the foundation for subsequent advances in audio-based search and autonomous systems. By tackling the underexplored problem of sound object localization, Yan Ke’s research has had lasting impact, inspiring further studies in auditory scene analysis and practical applications in surveillance, human-robot interaction, and content-based retrieval. Their innovative approach continues to influence researchers working at the intersection of audio processing and intelligent systems.

Research Focus

Key Achievements

1
H-Index
1
Papers
45
Total Citations
45
Avg Citations/Paper
🏆 Most Cited Paper
SOLAR: Sound Object Localization and Retrieval in Complex Audio Environments
45 citations · 2006
📈 Most Prolific Year: 2006 (1 Papers)
🤝 Key Collaborators: 2
🏛 Institutions: Carnegie Mellon University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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