This paper introduces a new Bayesian network structure, named a Partial Bayesian Network (PBN), and describes an algorithm for constructing it. The PBN is designed to be used for classification tasks, and accordingly the algorithm constructs an approximate Markov blanket around a classification node. Initial experiments have compared the performance of the PBN algorithm with Naïve Bayes, Tree-A...

Text-to-speech (TTS) synthesis is the text normalization from written input form to spoken output form, with applications in intelligent personal assistants (IPAs), voice-activated emails, and message readers for the visually impaired. In this project, we built a 3-component TTS text normalization system with token-to-token Naïve Bayes (NB) classifiers, a token-to-class Support Vector Machine (...

Word Sense Disambiguation (WSD) is the process of selecting a sense of an ambiguous word in a given context from a set of predefined senses. Sense Inventory usually comes from a dictionary or thesaurus. In Arabic, the main cause of word ambiguity is the lack of diacritics of the most digital documents so the same word can occurs with different senses. In this paper, we use the rooting algorithm...

Ensemble methods with Random Oracles have been proposed recently (Kuncheva and Rodŕıguez, 2007). A random-oracle classifier consists of a pair of classifiers and a fixed, randomly created oracle that selects between them. Ensembles of random-oracle decision trees were shown to fare better than standard ensembles. In that study, the oracle for a given tree was a random hyperplane at the root of ...

We present the system nFOIL. It tightly integrates the naı̈ve Bayes learning scheme with the inductive logic programming rule-learner FOIL. In contrast to previous combinations, which have employed naı̈ve Bayes only for post-processing the rule sets, nFOIL employs the naı̈ve Bayes criterion to directly guide its search. Experimental evidence shows that nFOIL performs better than both its base line...

in Continuous Domains Tapio Elomaa and Juho Rousu Department of Computer S ien e, University of Helsinki, Finland {elomaa,rousu} s.helsinki.fi Abstra t. Naïve Bayesian lassi ers assume the onditional independen e of attribute values given the lass. Despite this in pra ti e often violated assumption, these simple lassi ers have been found e ient, e e tive, and robust to noise. Dis retization of ...

Early gesture/action recognition is the task of determining the identity of a gesture/action with as few information as possible. Although the topic is relatively new, there are some methods that address this problem. However, existing methods rely on complex modeling procedures, that do not necessarily paid off the computational effort. Thus, simple yet effective and efficient techniques are r...

Many classes of images exhibit sparse structuring of statistical dependency. Each variable has strong statistical dependency with a small number of other variables and negligible dependency with the remaining ones. Such structuring makes it possible to construct a powerful classifier by only representing the stronger dependencies among the variables. In particular, a seminaïve Bayes classifier ...

The word sense disambiguation (WSD) is the task ofautomatically selecting the correct sense given a context and it helps in solving many ambiguity problems inherently existing in all natural languages.Statistical Natural Language Processing (NLP),which is based on probabilistic, stochastic and statistical methods, has been used to solve many NLP problems.The Naive Bayes algorithm which is one o...

This paper introduces the speech emotion corpus, a multilingual speech emotion database recorded in the provincial languages of Pakistan: Urdu, Punjabi, Pashto and Sindhi for analyzing the speech emotions present in the recorded speech signals with the four different emotions (Anger, Sadness, Comfort and Happiness). The objective of this paper is to evaluate the performance of the learning clas...