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Anatomical biasing and clicks: Evidence from biomechanical modeling
clicks hard palate alveolar ridge
2017/9/4
It has been observed by several researchers that the Khoisan palate tends to lack a prominent alveolar ridge. A biomechanical model of click production was created to examine if these sounds might be ...
Diversity not quantity in caregiver speech: Using computational modeling to isolate the effects of the quantity and the diversity of the input on vocabulary growth
Input quantity Lexical diversity Vocabulary acquisition
2017/8/30
Children who hear large amounts of diverse speech learn language more quickly than children who do not. However, high correlations between the amount and the diversity of the input in speech samples m...
There Is No Logical Negation Here, But There Are Alternatives: Modeling Conversational Negation with Distributional Semantics
Alternatives Distributional Semantics
2017/4/6
Logical negation is a challenge for distributional semantics, because predicates and their negations
tend to occur in very similar contexts, and consequently their distributional vectors are
very si...
Modeling language-learners’ errors in understanding casual speech
dictation task non-native perception computational modeling spoken word recognition
2016/5/3
In spontaneous conversations, words are often produced in reduced form compared to formal careful speech. In English, for instance, ’probably’ may be pronounced as ’poly’ and police’as ’plice’. Reduc...
DIANA: towards computational modeling reaction times in lexical decision in North American English
reaction times local speed participant-model comparison
2015/12/21
DIANA is an end-to-end computational model of speech processing, which takes as input the speech signal, and provides
as output the orthographic transcription of the stimulus, a
word/non-word judgme...
Adaptive Generation in Dialogue Systems Using Dynamic User Modeling
Adaptive Generation Dialogue Systems Dynamic User Modeling
2015/9/14
We address the problem of dynamically modeling and adapting to unknown users in resource-scarce domains in the context of interactive spoken dialogue systems. As an example, we show how a system can l...
Modeling Regular Polysemy:A Study on the Semantic Classification of Catalan Adjectives
Modeling Regular Polysemy Semantic Classification Catalan Adjectives
2015/9/10
We present a study on the automatic acquisition of semantic classes for Catalan adjectives from distributional and morphological information, with particular emphasis on polysemous adjectives. The aim...
Discriminative Word Alignment by Linear Modeling
Discriminative Word Alignment Linear Modeling
2015/9/8
Word alignment plays an important role in many NLP tasks as it indicates the correspondence between words in a parallel text. Although widely used to align large bilingual corpora, generative models a...
Modeling Local Coherence:An Entity-Based Approach
Modeling Local Coherence Entity-Based Approach
2015/9/6
This article proposes a novel framework for representing and measuring local coherence. Central to this approach is the entity-grid representation of discourse, which captures patterns of entity distr...
Using Topic Modeling to Improve Prediction of Neuroticism and Depression in College Students
Neuroticism Depression College Students
2015/9/2
We investigate the value-add of topic modeling in text analysis for depression, and for neuroticism as a stronglyassociated personality measure. Using Pennebaker’s Linguistic Inquiry and Word Count (L...
Sometimes Average is Best:The Importance of Averaging for Prediction using MCMC Inference in Topic Modeling
Sometimes Average is Best Averaging for Prediction MCMC Inference Topic Modeling
2015/9/2
Markov chain Monte Carlo (MCMC) approximates the posterior distribution of latent variable models bygenerating many samples and averaging over them. In practice, however, itis often more convenient to...
Beyond LDA:Exploring Supervised Topic Modeling for Depression-Related Language in Twitter
Beyond LDA Exploring Supervised Topic Modeling Depression-Related Language Twitter
2015/9/2
Topic models can yield insight into how depressed and non-depressed individuals use language differently. In this paper, we explore the use of supervised topic models in the analysis of linguistic sig...
A Machine Learning Approach to Modeling Scope Preferences
Machine Learning Approac Modeling Scope Preferences
2015/8/28
This article describes a corpus-based investigation of quantifier scope preferences. Following recent work on multimodular grammar frameworks in theoretical linguistics and a long history of combining...
Using Hidden Markov Modeling to Decompose Human-Written Summaries
Human-Written Summaries Hidden Markov
2015/8/27
Professional summarizers often reuse original documents to generate summaries. The task of summary sentence decomposition is to deduce whether a summary sentence is constructed by reusing
the origina...
Probabilistic Top-Down Parsing and Language Modeling
Probabilistic Top-Down Parsing Language Modeling
2015/8/26
This paper describes the functioning of a broad-coverage probabilistic top-down parser, and its application to the problem of language modeling for speech recognition. The paper first introduces key n...