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A Hebbian model of learning predicts that adults may be able to acquire a nonnative speech contrast if they are trained with stimuli that are exaggerated to make them perceptually distinct. To test th...
A paralleldistributed processing model of visual word recognitionand pronunciation is described. The model consists of sets of orthographic and phonologlc~ units and an interlevel of hidden units. Wei...
In a remarkable confirmation of OT in an empirical domain for which it was not originally intended, phonological and morphological variation has been successfully modeled by partially ranked categoric...
Learning to read and write requires an individual to connect additional orthographic representations to pre-existing mappings between phonological and semantic representations of words. Past empirical...
In this paper we use a computational model to investigate four assumptions that are tacitly present in interpreting the results of studies on infants’ speech processing abilities using the Headturn Pr...
A Sinusoidal Model Approach to Acoustic Landmark Detection and Segmentation for Robust Segment-Based Speech Recognition.
Style & Topic Language Model Adaptation Using HMM-LDA     styles  topics       font style='font-size:12px;'> 2015/3/10
Style & Topic Language Model Adaptation Using HMM-LDA.
Broad Phonetic Class Recognition in a Hidden Markov Model Framework Using Extended Baum-Welch Transformations.
A Back-off Discriminative Acoustic Model for Automatic Speech Recognition.
An Efferent-Inspired Auditory Model Front-End for Speech Recognition     efferent  auditory model       font style='font-size:12px;'> 2015/3/9
An Efferent-Inspired Auditory Model Front-End for Speech Recognition.
Handling Uncertain Observations in Unsupervised Topic-Mixture Language Model Adaptation.
Evaluation of Multi-level Context-Dependent Acoustic Model for Large Vocabulary Speaker Adaptation Tasks.
A Nonparametric Bayesian Approach to Acoustic Model Discovery.
Learning Lexicons From Speech Using a Pronunciation Mixture Model.
This report proposes a novel approach for Gaussian Mixture Model (GMM) weights decomposition and adaptation. This modeling suggests a new low-dimensional utterance representation method, which uses ...

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