speech pattern recognition using neural networks

... scale up to large speech recognition tasks This thesis demonstrates that neural networks can indeed form the basis for a general purpose speech recognition system, and that neural networks offer ... and a summary of related work in speech recognition and neural networks: • Chapter reviews the field of speech recognition • Chapter reviews the field of neural networks • Chapter reviews the intersection ... present approaches to speech recognition using neural networks The remainder of the thesis describes our own research, evaluating both predictive networks and classification networks as acoustic...

Ngày tải lên: 28/04/2014, 10:18

... scale up to large speech recognition tasks This thesis demonstrates that neural networks can indeed form the basis for a general purpose speech recognition system, and that neural networks offer ... and a summary of related work in speech recognition and neural networks: • Chapter reviews the field of speech recognition • Chapter reviews the field of neural networks • Chapter reviews the intersection ... present approaches to speech recognition using neural networks The remainder of the thesis describes our own research, evaluating both predictive networks and classification networks as acoustic...

Ngày tải lên: 13/08/2014, 02:21

... HMM is traditionally a generative model, even though we are using it for speech recognition The difference is moot 2 Review of Speech Recognition 18 contributes something to the total probability ... word recognition, it cannot be applied to continuous speech recognition, because it is impractical to have a separate HMM for each possible sentence In order to perform continuous speech recognition, ... argue that neural networks mitigate each of the above weaknesses (except the First Order Assumption), while they require relatively few parameters, so that a neural network based speech recognition...

Ngày tải lên: 13/08/2014, 02:21

... stored patterns by supplying any part of the pattern) ; • layered networks are useful for pattern association (i.e., mapping input vectors to output vectors); • recurrent networks are useful for pattern ... recognize patterns no matter where they occur in time Assuming the task is speech recognition, or some other task in the temporal domain 3.3 A Taxonomy of Neural Networks 39 The TDNN is trained using ... extent that the neural network may be simulated on a conventional computer, rather than implemented directly in hardware 3.2 Fundamentals of Neural Networks 29 In drawings of neural networks, units...

Ngày tải lên: 13/08/2014, 02:21

... infancy, and it is premature to rely on neural networks for temporal modeling in a speech recognition system 4.3 NN-HMM Hybrids We have seen that neural networks are excellent at acoustic modeling ... AlphaNet (final panel) tic modeling in neural networks In particular, neural networks are often trained to compute emission probabilities for HMMs Neural networks are well suited to this mapping ... which the speech frames are produced by a combination of signal analysis 4.3 NN-HMM Hybrids 63 and neural networks; the speech frames then serve as inputs for an ordinary HMM The neural networks...

Ngày tải lên: 13/08/2014, 02:21

... with continuous speech recognition were performed using an early version of the CMU Conference Registration database (Wood 1992) The database consists of 204 English sentences using a vocabulary ... receptionist who speaks no English Janus performs speech translation by integrating three modules — speech recognition, text translation, and speech generation — into a single end-to-end system ... The speech recognition module, for example, was originally implemented by our LPNN, described in Chapter (Waibel et al 1991, Osterholtz et al 1992); but it was later replaced by an LVQ-based speech...

Ngày tải lên: 13/08/2014, 02:21

... network Nonlinearity is a feature of neural networks in general, hence this is not an advantage of predictive networks over classification networks Although predictive networks yield a whole frame of ... Networks 81 6.3 Linked Predictive Neural Networks We explored the use of predictive networks as acoustic models in an architecture that we called Linked Predictive Neural Networks (LPNN), which was ... word recognition and continuous speech recognition 6.3.1 Basic Operation Predicted Speech Frame Predictor for /A/ (10 hidden units) Good Prediction ⇒ /A/ A Prediction Errors B A B Input Speech...

Ngày tải lên: 13/08/2014, 02:21

... this chapter we have seen that good word recognition accuracy can be achieved using neural networks that have been trained as speech classifiers However, the networks cannot be simply thrown at the ... specificity of the speech models for a given database is a timeconsuming process, and it is not specifically related to neural networks Therefore we did not make a great effort to optimize our speech models ... sentence recognition Linear word units, as Classification Networks 140 “CAT” Word w2 w1 w3 Test CAT Test CAT DTW Train copy A B C T Z Train A B C T Z copy TDNN hidden hidden Speech: “CAT” Speech: ...

Ngày tải lên: 13/08/2014, 02:21

... outperformed the pure HMM systems (CI-Sphinx and CI-Decipher), using a comparable number of parameters This supports our claim that neural networks make more efficient use of parameters than an HMM, ... primitive HMM, suggesting that predictive networks suffer severely from their lack of discrimination On the other hand, the HCNN (which is also based on predictive networks) achieved respectable results, ... between training and testing criteria It is with the MS-TDNN that we achieved a word recognition accuracy of 90.5% using only 67K parameters, significantly outperforming the context independent HMM...

Ngày tải lên: 13/08/2014, 02:21

... Speech Recognition In 1st International Conference on Neural Networks, IEEE [78] Lippmann, R (1989) Review of Neural Networks for Speech Recognition Neural Computation 1(1):1-38, Spring 1989 Reprinted ... alternate phoneme models 85, 95 ALVINN applications neural network speech recognition speech- to -speech translation 75 TDNN 38 architectures See neural networks ART1 and ART2 42 articulation 1, 76, ... Waibel, A (1990a) A Novel Objective Function for Improved Phoneme Recognition using Time Delay Neural Networks IEEE Trans on Neural Networks, 1(2), June 1990 [41] Hampshire, J and Pearlmutter, B...

Ngày tải lên: 13/08/2014, 02:21

... 1 Information Theory, Pattern Recognition and Neural Networks Approximate roadmap for the eight-week course in Cambridge Lecture Before ... 391 418 421 434 449 450 458 471 473 475 479 482 484 Neural networks 491 42 Introduction to Neural Networks 43 The Single Neuron as a Classifier ... called the ‘K-L distance’, is not strictly a ‘distance’ This quantity is important in pattern recognition and neural networks, as well as in information theory Gibbs’s inequality is probably the most...

Ngày tải lên: 28/04/2014, 09:52

Ngày tải lên: 28/04/2014, 09:59

Ngày tải lên: 03/09/2012, 15:54

... design retrieval system using neural networks, IEEE Transactions on Neural Networks, 8(4):847-851 Tseng, Y.-J., (1999) A modular modeling approach by integrating feature recognition and feature-based ... unsupervised as well as adaptive neural networks In response to both analog and binary input patterns, fuzzy ART incorporates an important feature of ART models, such as the pattern matching between ... memory with back-propagation neural networks and adaptive resonance theory (Bahrami et al., 1995) Lin and Chang (1996) combine fuzzy set theory and back-propagation neural networks to deal with uncertainty...

Ngày tải lên: 17/12/2013, 06:15

... box’ approach Process Overview Using Neural Networks in HYSYS Using Neural Networks in HYSYS Steps for using Neural Networks in HYSYS The procedure for using Neural Networks in HYSYS is as follows: ... and case studies Using Neural Networks in HYSYS Neural Networks What is a Neural Network? A Neural Network (strictly an ‘Artificial Neural Network’ as opposed to a ‘Biological Neural Network’) ... could include large errors Neural Networks will not predict the effect of changes in variables not included in the training data 11 Using Neural Networks in HYSYS Exercise Using the Parametric Unit...

Ngày tải lên: 23/03/2014, 02:20

... Tracking(PAST) System Using Neural Networks 122 xv List of Tables LIST OF TABLES Page Table 5.1: Training from Initial Set of Weights DC motor Position and Speed Tracking(PAST) System Using Neural Networks ... System Using Neural Networks vii Summary SUMMARY The aim of this thesis is to develop a high performance, position and speed tracking (PAST) system for a DC motor using an artificial neural network ... Using Neural Networks 10 Chapter 2: Literature Review 2.2 Artificial Neural Network – Rule Base In this method, Soliman et al., (1994) used a simple algorithm for ANN-based speed regulation using...

Ngày tải lên: 04/10/2015, 10:25

... recognition in particular Recognition rate significantly increate when using additional spell checker module Neural network for a recognition system In the traditional model of pattern recognition, a hand-designed ... pattern will be transferred to the next network until the system can recognize it correctly Figure 3: Convolution neural network with unknown output Figure 4: Recognition System using multi neural ... convolution neural network (CNN) solves this shortcoming of traditional one to achieve the best performance on pattern recognition task The CNNs is a special form of multi-layer neural network...

Ngày tải lên: 28/04/2014, 10:11

... statistical pattern recognition which I regard as essential for a clear understanding of neural networks More extensive treatments of these topics can be found in the many texts on statistical pattern recognition, ... underpinnings of neural networks Historically, many concepts in neural computing have been inspired by studies of biological networks The perspective of statistical pattern recognition, however, ... Index 477 STATISTICAL PATTERN RECOGNITION The term pattern recognition encompasses a wide range of information processing problems of great practical significance, from speech recognition and the...

Ngày tải lên: 24/04/2014, 14:04

... moved appropriately [9] 1.4 An Acoustic Speech to Visual Speech Synthesizer A system that reliably translates natural auditory speech into synthetic visible speech would normally require the following ... given the auditory speech There are several labeled databases of auditory speech but no readily available labeled databases of visual speech Given the lack of databases for visible speech, investigators ... from the auditory speech to these specific movements We determined the mapping between the acoustic speech and the appropriate visual speech movements by training an artificial neural network to...

Ngày tải lên: 28/04/2014, 10:06

... 9: False recognition probability versus SNR (a) Inter-class recognition (Case I) (b) Inter-class recognition (Case II) (c) Intraclass PSK recognition (d) Intra-class FSK recognition recognition ... Inter-class recognition Full-class recognition Intra-class FSK recognition Intra-class QAM recognition Figure 10: False recognition probability versus number of symbols (inter-class recognition, ... total recognition percentage using several wavelet filters in the case of full-class recognition for SNR = dB Using Haar wavelet, our previous results show that the SNRmin for full-class recognition...

Ngày tải lên: 21/06/2014, 16:20