Listeners use their lexical knowledge to interpret ambiguous sounds, and retune their phonetic categories to include this ambiguous sound. Although there is ample evidence for lexically-guided retuning, the adaptation process is not fully understood. Using a lexical decision task with an embedded auditory semantic priming task, the present study investigates whether words containing an ambiguou...

In this paper we present an “emotional storyteller robot”: a robot that is capable to tell story in an attractive way using the appropriate affective intonation concerning the piece of story that it’s telling. Our approach is inspired by Taghard’s theory about the human ability to find emotional analogies between the situation described in a piece of text and the past experience of the reader i...

We present Multi-Relational Latent Semantic Analysis (MRLSA) which generalizes Latent Semantic Analysis (LSA). MRLSA provides an elegant approach to combining multiple relations between words by constructing a 3-way tensor. Similar to LSA, a lowrank approximation of the tensor is derived using a tensor decomposition. Each word in the vocabulary is thus represented by a vector in the latent sema...

The constituents of English compounds (e.g., butter and fly for butterfly) and two-character Chinese words may differ in meaning from the whole word. Furthermore, the meanings of the words containing the same constituent (e.g., butter in “butterfingers”, or “buttermilk”) may or may not be consistent. Estimating semantic transparency of a constituent is usually difficult and subjective because o...

A new approach for constructing pseudo-keywords, referred to as Sense Units, is proposed. Sense Units are obtained by a word clustering process, where the underlying similarity reflects both statistical and semantic properties, respectively detected through Latent Semantic Analysis and WordNet. Sense Units are used to recode documents and are evaluated from the performance increase they permit ...

This paper takes a critical look at theory-free, statistical methodologies for processing and interpreting data taken from respondents answering a set of dichotomous (yes-no) questions. The basic issue concerns to what extent theoretical conclusions based on such analyses are invariant under a class of "informationally equivalent" question transformations. First the notion of Boolean equivalenc...

Multi-view data is common in a wide variety of application domains. Properly exploiting the relations among different views is helpful to alleviate the difficulty of a learning problem of interest. To this end, we propose an extended Probabilistic Latent Semantic Analysis (PLSA) model for multi-view clustering, named Co-regularized PLSA (CoPLSA). CoPLSA integrates individual PLSAs in different ...

Non-negative matrix factorization (NMF) has become quite popular recently on the relational data due to its several nice properties and connection to probabilistic latent semantic analysis (PLSA). However, few algorithms take this route for the heterogeneous networks. In this paper we propose a novel clustering method for heterogeneous information networks by searching for a factorization that ...

In this paper, we present an object recognition approach that in addition allows to discover intra-class modalities exhibiting highcorrelated visual information. Unlike to more conventional approaches based on computing multiple specialized classi ers, the proposed approach combines a single classi er, Boosted Random Ferns (BRFs), with probabilistic Latent Semantic Analysis (pLSA) in order to r...