The aim of this report was to implement a text-dependent speaker verification system using speaker adapted neural networks and to evaluate the system. The idea was to use a hybrid HMM/ANN approach, i.e. Artificial Neural Networks were used to estimate Hidden Markov Model emission posterior probabilities from speech data, and the system was implemented in C++ as a module for GIVES. The report al...

In traditional help desk service centres, service engineers provide a world-wide customer support service through the use of long-distance telephone calls. Such a mode of support is found to be inefficient, ineffective and generally results in high costs, long service cycles, and poor quality of service. With the advent of Internet technology, it is possible to deliver customer service support ...

| In this paper we report a series of tests carried out on our hybrid HMM/ANN systems which aims at combining Neural Networks theory and Hidden Markov Models (HMMs) for speech recognition of a continuous speech French database: BREF-80. As this database is not manually labelled , we describe a new method based on the temporal alignment of the speech signal on a high quality synthetic speech pat...

We propose a technique for generating alternative models for keywords in a hybrid hidden Markov model artificial neural network (HMM-ANN) keyword spotting paradigm. Given a base pronunciation for a keyword from the lookup dictionary, our algorithm generates a new model for a keyword which takes into account the systematic errors made by the neural network and avoiding those models that can be c...

this paper investigates the forecasting gold coin futures contract price in iran mercantile exchange. this research has presented a hybrid model based on genetic fuzzy systems (gfs) and artificial neural network (ann) to forecast the gold futures contract, at first, we use stepwise regression analysis (sra) to determine factors which have most influence on stock prices. at the next stage we div...

We consider the problem of automatic genome segmentation (AGS) that aims to assign discrete labels to all genomic regions based on multiple ChIP-seq samples. We propose to use a hybrid model that combines a hidden Markov model (HMM) with an artificial neural network (ANN) to overcome the weaknesses of a standard HMM. Our contributions are threefold: first, we benchmark two approaches to generat...

In this paper we present a system for audio-visual speech recognition based on a hybrid Artificial Neural Network/Hidden Markov Model (ANN/HMM) approach. To setup the system it was necessary to record a new audio-visual database. We will describe the recording and labeling of the database. The fusion of audio and video data is a key aspect of the paper. Three conditions, when only the audio or ...

In this paper we present a system for audio-visual speech recognition based on a hybrid Artificial Neural Network/Hidden Markov Model (ANN/HMM) approach. To setup the system it was necessary to record a new audio-visual database. We will describe the recording and labeling of the database. The fusion of audio and video data is a key aspect of the paper. Three conditions, when only the audio or ...

in this paper, the prediction of future stock close price of SENSEX & NSE stock exchange is found using the proposed Hybrid ANN model of Functional Link Fuzzy Logic Neural Model. The historic raw data’s of SENSEX & NSE stock exchange has been pre-processed to the range of (0 to 1). After pre-processing the inputs and forwarded to functional expansion function to perform neural operation. The ac...

Because of the application of the Hidden Markov Model (HMM) in acoustic modeling, a significant breakthrough has been made in recognizing continuous speech with a large glossary. However, some unreasonable hypotheses for acoustic modeling and the unclassified training algorithm on which the HMM based form a bottleneck, restricting the further improvement in speech recognition. The Artificial Ne...