Xiang-Lilan Zhang

Papers

Total Citations

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About

Xiang-Lilan Zhang is a researcher whose work bridges the frontiers of speech recognition and signal processing. Her most-cited contribution, "Merge-Weighted Dynamic Time Warping for Speech Recognition" (2014), introduces an innovative algorithm that refines the classic Dynamic Time Warping method by incorporating weighted merging strategies. This approach enhances the accuracy and efficiency of aligning temporal sequences, a fundamental challenge in speech recognition systems. While her citation count of 9 for this paper reflects a focused, specialized impact, the work demonstrates a keen ability to optimize core computational techniques for real-world applications. Zhang’s research contributes to the broader goal of making speech technology more robust and adaptive, particularly in handling variable speaking rates and noisy environments. Her methodological insights offer valuable tools for researchers in pattern recognition and human-computer interaction. Though her publication record is concise, it underscores a commitment to advancing the theoretical and practical underpinnings of speech processing, marking her as a thoughtful contributor to this evolving field.