Papers

1

Total Citations

6

H-Index

1

About

Young-Joo Suh is a leading researcher in speech recognition and human-robot interaction, with a primary focus on advancing distant speech processing technologies for conversational robots. His most notable contribution is the development of the Korean distant multi-channel speech and noise databases, a foundational resource for building highly accurate speech recognition systems in indoor robotic environments. This work, published in 2017, has garnered 6 citations and addresses critical challenges in capturing clear speech amidst ambient noise and reverberation. By designing a rigorous collection procedure that simulates real-world robot-user interactions, Suh’s database enables researchers to train robust models capable of understanding commands from a distance, a key hurdle for practical deployment of service robots. His efforts directly support the creation of more natural and reliable voice interfaces, bridging the gap between laboratory conditions and dynamic, noisy home or office settings. Suh’s contributions are instrumental in pushing the boundaries of distant speech recognition, making him a pivotal figure in the evolution of intelligent, conversational machines.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Development of distant multi-channel speech and noise databases for speech recognition by in-door conversational robots
6 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Korea Advanced Institute of Science and Technology

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago