Sani Salisu
Papers
1
Total Citations
8
H-Index
1
About
Sani Salisu is a researcher at the forefront of human-robot interaction (HRI), with a focused expertise in developing intuitive speech recognition models for robotic platforms. His most cited work, "A New Speech Recognition Model in a Human-Robot Interaction Scenario Using NAO Robot: Proposal and Preliminary Model" (2021), has garnered 8 citations, establishing a foundational contribution to the field. In this pivotal study, Salisu addresses a critical challenge in HRI: the distinction between automatic speech recognition (ASR) and voice recognition, proposing a novel model tailored for the NAO robot. His work clarifies the technical nuances of converting spoken language into actionable commands for social robots, moving beyond simple speech-to-text conversion to enable more natural, context-aware interactions. By tackling the complexities of single-user voice differentiation, Salisu’s research lays essential groundwork for more responsive and adaptive robotic assistants. His contributions are particularly valuable for students and researchers exploring the intersection of robotics, artificial intelligence, and natural language processing, offering a clear pathway toward more seamless human-machine communication.
Research Focus
Key Achievements
Top Papers
- 1