In this paper, we will describe several extensions to our earlier work, utilizing a segment-based approach. We will formulate our segmental framework and report our study on the use of multi-layer perceptrons for detection and classification of phonemes. We will also examine the outputs of the network, and compare the network performance with other classifiers. Our investigation is performed wi...

This paper reports an investigation of features relevant for classifying two speaking styles, namely, conversational speaking style and clear (e.g. hyper-articulated) speaking style. Spectral and prosodic features were automatically extracted from speech and classified using decision tree classifiers and multilayer perceptrons to achieve accuracies of about 71% and 77% respectively. More intere...

This paper investigates the hypothesis that cues involving the positioning of the lips may improve upon a system that performs a mapping from acoustic parameters to electropalatographic (EPG) information; that is, patterns of contact between the tongue and the hard palate. We adopt a multilayer perceptron as a relatively simple model for the acoustic-toelectropalatographic mapping and demonstra...

We describe a wordspotting algorithm based on a predictive neural model for a telephone speech corpus. Each keyword is modeled as a whole word. For keyword detection scoring we used a minimum accumulated prediction residual. We computed empirically a threshold value for rejecting non-keyword speech in place of building non-keyword models. We tested the algorithm with the TUBTEL telephone speech...

In this study, we propose a multi-layer perceptron with a glial network which is inspired from the features of glias in the brain. All glias in the proposed network generate independent oscillations, and the oscillations propagate through the glial network with attenuation. We apply the proposed network to the two-spiral problem. Computer simulations show that the proposed network gains a bette...

Abs t r ac t . Diabetes is the most common disease nowadays in all populations and in all age groups. Different techniques of artificial intelligence has been applied to diabetes problem. This research proposed the artificial metaplasticity on multilayer perceptron (AMMLP) as prediction model for prediction of diabetes. The Pima Indians diabetes was used to test the proposed model AMMLP. The re...

The prediction of bursty events on the internet is a challenging task. Difficulties are due to the diversity of information sources, the size of the internet, dynamics of popularity, user behaviors... On the other hand, Twitter is a structured and limited space. In this paper, we present a bursty event prediction method applied to the Twitter plateform. The proposed method uses tweet contents t...

The problem of selecting the best set of features for target recognition using a multilayer perceptron is addressed in this paper. A technique has been developed which analyzes the weights in a multilayer perceptron to determine which features the network finds important and which are unimportant. A brief introduction to the use of multilayer perceptrons for classification and the training rule...

Abstract. Dry Low Emission (DLE) gas turbine has been developed as a solution to encounter the harmful high NOx emission from conventional turbine. However, it is prone create Lean Blowout (LBO) error that causes frequent shutdown due its stringent condition needs be operate inside desired operating can monitored through temperature, and CO concentration. This paper develops an Artificial Neura...

This postulate was experimentally confirmed in the hippocampus, where high-frequency stimulation (HFS) of a presynaptic neuron causes long-term potentiation (LTP) in the synapses connecting it to the postsynaptic neurons (Bliss and Lomo, 1973). LTP takes place only if the postsynaptic cell is also active and sufficiently depolarized (Kelso et al., 1986). In many brain areas, this is due to the ...