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About

Misako Goto is a researcher whose work sits at the intersection of cybersecurity and cognitive linguistics, focusing on innovative CAPTCHA systems that leverage human auditory perception. Her primary research area involves designing text-based CAPTCHAs that exploit the phonemic restoration effect—a psychological phenomenon where the brain "fills in" missing sounds in speech—combined with similar pronunciation patterns, particularly those found in Asian accents. Goto’s major contribution is the development of audio-based Turing tests that are more resistant to automated speech recognition bots while remaining accessible to human users. Her most-cited paper, "Text-Based CAPTCHA Using Phonemic Restoration Effect and Similar Pronunciation with an Asian Accent" (2014), has garnered 21 citations, establishing a foundation for human-centric security challenges. She further refined this approach in subsequent works, including an HTK (Hidden Markov Model Toolkit) analysis (2015), which validated the robustness of her system against machine attacks. By integrating linguistic nuances and perceptual psychology, Goto has advanced the field of web security, offering a novel countermeasure against bots that threaten online services through spam, phishing, and account fraud. Her work remains a key reference for researchers exploring audio CAPTCHA design and human-machine differentiation.