Broad phonetic classification using discriminative Bayesian networks

اسناد مشابه

• Broad phonetic classification using discriminative Bayesian networks

  سند علمی۲۰۰۹Speech CommunicationFranz Pernkopf, Tuan Van Pham, Jeff A. Bilmes

  We present an approach to broad phonetic classification, defined as mapping acoustic speech frames into broad (or clustered) phonetic categories. Our categories consist of silence, general voiced, general unvoiced, mixed sounds, voiced closure, and plosive release, and are suffic

• A new HMM-based approach to broad phonetic classification of speech

  سند علمی۲۰۰۳INTERSPEECHJouni Pohjalainen

  A novel automatic method is introduced for classifying speech segments into broad phonetic categories using one or more hidden Markov models (HMMs) on long speech utterances. The general method is based on prior analysis of the acoustic features of speech and the properties of HM

• Multi - label classification with Bayesian network - based chain classifiers q

  سند علمی۲۰۱۵L. Enrique Sucar, Concha Bielza, Eduardo F. Morales, Pablo Hernandez-Leal

  In multi-label classification the goal is to assign an instance to a set of different classes. This task is normally addressed either by defining a compound class variable with all the possible combinations of labels (label power-set methods) or by building independent classifier

• Improving Classification in Bayesian Networks using Structural Learning

  سند علمی۲۰۱۱

  Naïve Bayes classifiers are simple probabilistic classifiers. Classification extracts patterns by using data file with a set of labeled training examples and is currently one of the most significant areas in data mining. However, Naïve Bayes assumes the independence among the fea

• Remote Sensing Image Classification by Bayesian Network Classifier Based on Causality

  سند علمی۲۰۱۴Li Xiang

  It has always been a hotspot and difficult point in remote sensing to identify interesting geographical objects from remote sensing images. To reduce the independence between the random variables in the network Bayesian classifier model and to improve the classification performan

• Likelihood-Based Robust Classification with Bayesian Networks

  سند علمی۲۰۱۲IPMUAlessandro Antonucci, Marco E. G. V. Cattaneo, Giorgio Corani

  Bayesian networks are commonly used for classification: a structural learning algorithm determines the network graph, while standard approaches estimate the model parameters from data. Yet, with few data the corresponding assessments can be unreliable. To gain robustness in this