Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...

Hidden Markov Models (HMMs) are widely used in pattern recognition applications, most notably speech recognition. Speech samples are recorded using a wave surfer tool. Wave surfer is a simple but powerful interface. The sound can be visualized and analyzed in several ways with the help of this tool. The recorded signal (test data) is compared with the original signal (trained data) using Hidden...

many researchers adopt local binary pattern for pattern analysis. however, the long histogram created by local binary pattern is not suitable for large-scale facial database. this paper presents a simple facial pattern descriptor for facial expression recognition. local pattern is computed based on local gradient flow from one side to another side through the center pixel in a 3x3 pixels region...

In this paper, a new solution to the inverse problem of iterated random function systems is presented. The solution is based on a generalized hidden Markov model formalism to model the process generated by an iterated random function system. Instead of the assumption of conditional independence of observation sequence elements given the state sequence, the new model assumes the existence of sho...

In this paper, we demonstrate how a network of dendrites can be used to build the state decoding block of a wordspotter similar to a Hidden Markov Model (HMM) classifier structure. We present simulation and experimental data for a single line dendrite and also experimental results for a dendrite-based classifier structure. This work builds on previously demonstrated building blocks of a neural ...

This paper describes a technique for behavioral and temporal pattern detection within financial data, such as credit card and bank account data, where the required information is only partially visible. Typically, transaction amount, transaction date, merchant name and type, and location of transaction are all visible data items, i.e., they are readily available in the financial institutions da...

Predicting the next request of a user as she visits Web pages has gained importance as Web-based activity increases. There are a number of different approaches to prediction. Markov models and their variations, collaborative filtering models, or models based on pattern recognition techniques such as sequence mining, association rule mining, clustering user sessions or user, have been found well...

We propose a coupled hidden Markov model (CHMM) approach to video-realistic speech animation, which realizes realistic facial animations driven by speaker independent continuous speech. Different from hidden Markov model (HMM)-based animation approaches that use a singlestate chain, we use CHMMs to explicitly model the subtle characteristics of audio–visual speech, e.g., the asynchrony, tempora...

Face recognition has established itself as an important subbranch of pattern recognition within the field of computer science. Many state-of-the-art systems have focused on the task of recognizing frontal views of people. In this work we will present an approach to recognize profile views (90 ) with a system trained on transformed frontal views. The system combines an Artificial Neural Network ...