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Bottom-up modeling of phoneme learning: Universal sensitivity and language-specific transformation” published in Speech Communication
Steven Chan2025-12-06T12:28:42+08:00“Bottom-up modeling of phoneme learning: Universal sensitivity and language-specific transformation” published in Speech Communication We are pleased to announce the publication of a new paper titled “Bottom-up modeling of phoneme learning: Universal sensitivity and language-specific transformation” in the journal Speech Communication. This study was conducted by Frank and Youngah. The research investigates the emergence and development of universal phonetic sensitivity during early phonological learning using an unsupervised modeling approach. The authors trained autoencoder models on raw acoustic input from English and Mandarin to simulate bottom-up perceptual development, focusing on phoneme contrast learning. The results demonstrate that phoneme-like categories and feature-aligned [...]