Sander Goetzee
Papers
1
Total Citations
3
H-Index
1
About
Sander Goetzee is a researcher at the intersection of human-robot interaction (HRI) and multimodal perception, with a primary focus on audio-visual speech recognition (AVSR) for social robotics. His most cited work, "Audio-Visual Speech Recognition for Human-Robot Interaction: a Feasibility Study" (2024, 3 citations), addresses a critical gap in the field: while visual speech recognition (VSR) models have achieved impressive results on benchmark datasets like LRS3 and LRS2, they have rarely been deployed on social robots. Goetzee’s study pioneers the feasibility of integrating AVSR into real-world robotic platforms, demonstrating how lip-reading and audio cues can be combined to improve speech recognition accuracy in noisy environments—a common challenge for robots operating in dynamic social settings. This contribution is particularly notable for bridging the gap between state-of-the-art VSR algorithms and practical HRI applications. By highlighting the limitations of existing models when applied to robotic contexts, Goetzee’s work lays the groundwork for more robust, perception-aware social robots. His research holds promise for enhancing communication in assistive robotics, public service robots, and other domains where reliable speech understanding is essential.
Research Focus
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Top Papers
- 1