“Attention-LSTM autoencoder simulation for phonotactic learning from raw audio input” published in Linguistics Vanguard
Steven Chan2025-09-19T11:41:30+08:00“Attention-LSTM autoencoder simulation for phonotactic learning from raw audio input” published in Linguistics Vanguard We are pleased to announce the publication of a new paper by Frank Lihui Tan and Youngah Do in the journal Linguistics Vanguard. The paper, titled “Attention-LSTM autoencoder simulation for phonotactic learning from raw audio input,” explores a novel approach to phonotactic learning using an attention-based long short-term memory (LSTM) autoencoder trained on raw audio input. Unlike previous models that rely on abstract phonological representations, this study simulates early phonotactic acquisition stages by processing continuous acoustic signals. The research focuses on an English phonotactic pattern, specifically [...]