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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 What do RNN Language Models Learn about Filler–Gap Dependencies? Wilcox, Ethan; Levy, Roger; Morita, Takashi... In: Association for Computational Linguistics (2021) BASE Show details 2 Measuring context dependency in birdsong using artificial neural networks Morita, Takashi; Koda, Hiroki; Okanoya, Kazuo... In: PLoS Comput Biol (2021) BASE Show details 3 Exploring TTS without T Using Biologically/Psychologically Motivated Neural Network Modules (ZeroSpeech 2020) ... Morita, Takashi; Koda, Hiroki. - : arXiv, 2020 Abstract: In this study, we reported our exploration of Text-To-Speech without Text (TTS without T) in the Zero Resource Speech Challenge 2020, in which participants proposed an end-to-end, unsupervised system that learned speech recognition and TTS together. We addressed the challenge using biologically/psychologically motivated modules of Artificial Neural Networks (ANN), with a particular interest in unsupervised learning of human language as a biological/psychological problem. The system first processes Mel Frequency Cepstral Coefficient (MFCC) frames with an Echo-State Network (ESN), and simulates computations in cortical microcircuits. The outcome is discretized by our original Variational Autoencoder (VAE) that implements the Dirichlet-based Bayesian clustering widely accepted in computational linguistics and cognitive science. The discretized signal is then reverted into sound waveform via a neural-network implementation of the source-filter model for speech production. ... : Accepted in INTERSPEECH 2020 ... Keyword: Audio and Speech Processing eess.AS; Computation and Language cs.CL; FOS Computer and information sciences; FOS Electrical engineering, electronic engineering, information engineering; Machine Learning cs.LG; Sound cs.SD URL: https://arxiv.org/abs/2005.05487 https://dx.doi.org/10.48550/arxiv.2005.05487 BASE Hide details 4 Unsupervised learning of lexical subclasses from phonotactics Morita, Takashi, Ph. D. Massachusetts Institute of Technology. - : Massachusetts Institute of Technology, 2018 BASE Show details 5 RNNs as psycholinguistic subjects: Syntactic state and grammatical dependency ... Futrell, Richard; Wilcox, Ethan; Morita, Takashi. - : arXiv, 2018 BASE Show details 6 Scalar implicatures in non-monotonic environments Morita, Takashi In: Semantics and Linguistic Theory; Proceedings of SALT 26; 205-223 ; 2163-5951 (2016) BASE Show details

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