Zhigang Luo

National University of Defense Technology

Papers

Total Citations

H-Index

About

Zhigang Luo is a researcher specializing in speech recognition, human-computer interaction, and gesture-based control systems. His work focuses on developing robust algorithms for automatic speech recognition (ASR) in challenging environments, particularly through language-independent and speaker-dependent approaches. Luo’s most notable contribution is the "One-against-All Weighted Dynamic Time Warping" method, which addresses the critical problem of recognizing seldom-used English words and non-English names in adverse conditions, achieving 16 citations. This work offers a lightweight, privacy-conscious solution for personalized ASR without extensive training data. Additionally, Luo has advanced ego-centric hand gesture analysis for robot control, presenting a multi-stage pipeline that enables natural, wearable-based interaction (9 citations). His "Merge-Weighted Dynamic Time Warping" further refines speech recognition accuracy (9 citations). With a combined impact of over 30 citations across his top papers, Luo’s research bridges the gap between robust speech processing and intuitive human-robot interfaces, making significant strides in real-world, privacy-sensitive applications. His work is particularly relevant for researchers exploring adaptive, low-resource ASR and wearable gesture recognition systems.