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Speech Recognition Using Hidden Markov Models With Exponential Interpolation Of State Parameters
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Book Synopsis Speech Recognition Using Hidden Markov Models with Exponential Interpolation of State Parameters by : Adam Wieworka
Download or read book Speech Recognition Using Hidden Markov Models with Exponential Interpolation of State Parameters written by Adam Wieworka and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Speech recognition using Hidden Markov Models with exponential interpolation by : Adam Wiewiorka
Download or read book Speech recognition using Hidden Markov Models with exponential interpolation written by Adam Wiewiorka and published by . This book was released on 1997 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Application of Hidden Markov Models in Speech Recognition by : Mark Gales
Download or read book The Application of Hidden Markov Models in Speech Recognition written by Mark Gales and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
Book Synopsis Hidden Markov Models by : Przemyslaw Dymarski
Download or read book Hidden Markov Models written by Przemyslaw Dymarski and published by BoD – Books on Demand. This book was released on 2011-04-19 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hidden Markov Models (HMMs), although known for decades, have made a big career nowadays and are still in state of development. This book presents theoretical issues and a variety of HMMs applications in speech recognition and synthesis, medicine, neurosciences, computational biology, bioinformatics, seismology, environment protection and engineering. I hope that the reader will find this book useful and helpful for their own research.
Book Synopsis Factorial Hidden Markov Models for Speech Recognition by : Beth Logan
Download or read book Factorial Hidden Markov Models for Speech Recognition written by Beth Logan and published by . This book was released on 1997 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :Yves Normandin Publisher :National Library of Canada = Bibliothèque nationale du Canada ISBN 13 : Total Pages :180 pages Book Rating :4.:/5 (318 download)
Book Synopsis Hidden Markov Models, Maximum Mutual Information Estimation, and the Speech Recognition Problem by : Yves Normandin
Download or read book Hidden Markov Models, Maximum Mutual Information Estimation, and the Speech Recognition Problem written by Yves Normandin and published by National Library of Canada = Bibliothèque nationale du Canada. This book was released on 1991 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings written by and published by . This book was released on 1997 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Study of the Hidden Markov Model in Speech Recognition by : Joseph Y. Fang
Download or read book Study of the Hidden Markov Model in Speech Recognition written by Joseph Y. Fang and published by . This book was released on 1988 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Robust Speech Recognition Using Hidden Markov Models by : Clifford Joseph Weinstein
Download or read book Robust Speech Recognition Using Hidden Markov Models written by Clifford Joseph Weinstein and published by . This book was released on 1990 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report presents an overview of a program of speech recognition research which was initiated in 1985 with the major goal of developing techniques for robust high performance speech recognition under the stress and noise conditions typical of a military aircraft cockpit. The work on recognition in stress and noise during 1985 and 1986 produced a robust Hidden Markov Model (HMM) isolated-word recognition (IWR) system with 99 percent speaker-dependent accuracy for several difficult stress/noise data bases, and very high performance for normal speech. Robustness techniques which were developed and applied include multi-style training, robust estimation of parameter variances, perceptually-motivated stress-tolerant distance measures, use of time-differential speech parameters, and discriminant analysis. These techniques and others produced more than an order-of-magnitude reduction in isolated-work recognition error rate relative to a baseline HMM system. An important feature of the Lincoln HMM system has been the use of continuous-observation HMM techniques, which provide a good basis for the development of the robustness techniques, and avoid the need for a vector quantizer at the input to the HMM system. Beginning in 1987, the robust HMM system has been extended to continuous speech recognition for both speaker-dependent and speaker-independent tasks. The robust HMM continuous speech recognizer was integrated in real-time with a stressing simulated flight task, which was judged to be very realistic by a number of military pilots. (kr).
Book Synopsis Shared-distribution Hidden Markov Models for Speech Recognition by : Carnegie-Mellon University. Computer Science Dept
Download or read book Shared-distribution Hidden Markov Models for Speech Recognition written by Carnegie-Mellon University. Computer Science Dept and published by . This book was released on 1991 with total page 22 pages. Available in PDF, EPUB and Kindle. Book excerpt: Here, output distributions in the hidden Markov model are shared with each other if they exhibit acoustic similarity. In addition to detailed representation, it also gives us the freedom to use a large number of states for each phonetic model. Although an increase in the number of states will increase the total number of free parameters, with distribution sharing we can essentially eliminate those redundant states and have the luxury to maintain necessary ones. By using the shared-distribution model, the error rate on the DARPA Resource Management task has been reduced by 20% in comparison with the baseline SPHINX system."
Book Synopsis Real-time Speech Recognition Using Hidden Markov Models by : Michael Mason
Download or read book Real-time Speech Recognition Using Hidden Markov Models written by Michael Mason and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Connectionist Speech Recognition by : Hervé A. Bourlard
Download or read book Connectionist Speech Recognition written by Hervé A. Bourlard and published by Springer Science & Business Media. This book was released on 1994 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.
Book Synopsis Hidden Markov Models for Speech Recognition by : X. D. Huang
Download or read book Hidden Markov Models for Speech Recognition written by X. D. Huang and published by . This book was released on 1990-01-01 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Isolated-word Speech Recognition System Using Hidden Markov Models by : William A. Bella
Download or read book An Isolated-word Speech Recognition System Using Hidden Markov Models written by William A. Bella and published by . This book was released on 1989 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis An Integrated Approach to Feature Compensation Combining Particle Filters and Hidden Markov Models for Robust Speech Recognition by : Aleem Mushtaq
Download or read book An Integrated Approach to Feature Compensation Combining Particle Filters and Hidden Markov Models for Robust Speech Recognition written by Aleem Mushtaq and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The performance of automatic speech recognition systems often degrades in adverse conditions where there is a mismatch between training and testing conditions. This is true for most modern systems which employ Hidden Markov Models (HMMs) to decode speech utterances. One strategy is to map the distorted features back to clean speech features that correspond well to the features used for training of HMMs. This can be achieved by treating the noisy speech as the distorted version of the clean speech of interest. Under this framework, we can track and consequently extract the underlying clean speech from the noisy signal and use this derived signal to perform utterance recognition. Particle filter is a versatile tracking technique that can be used where often conventional techniques such as Kalman filter fall short. We propose a particle filters based algorithm to compensate the corrupted features according to an additive noise model incorporating both the statistics from clean speech HMMs and observed background noise to map noisy features back to clean speech features. Instead of using specific knowledge at the model and state levels from HMMs which is hard to estimate, we pool model states into clusters as side information. Since each cluster encompasses more statistics when compared to the original HMM states, there is a higher possibility that the newly formed probability density function at the cluster level can cover the underlying speech variation to generate appropriate particle filter samples for feature compensation. Additionally, a dynamic joint tracking framework to monitor the clean speech signal and noise simultaneously is also introducedto obtain good noise statistics. In this approach, the information available from clean speech tracking can be effectively used for noise estimation. The availability of dynamic noise information can enhance the robustness of the algorithm in case of large fluctuations in noise parameters within an utterance. Testing the proposed PF-based compensation scheme on the Aurora 2 connected digit recognition task, we achieve an error reduction of 12.15% from the best multi-condition trained models using this integrated PF-HMM framework to estimate the cluster-based HMM state sequence information. Finally, we extended the PFC framework and evaluated it on a large-vocabulary recognition task, and showed that PFC works well for large-vocabulary systems also.
Book Synopsis Real-time Speech Recognition with Style Compensation Using Hidden Markov Models by : Abdul Ghaffar
Download or read book Real-time Speech Recognition with Style Compensation Using Hidden Markov Models written by Abdul Ghaffar and published by . This book was released on 1994 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Speech Recognition Using Hidden Markov Model by :
Download or read book Speech Recognition Using Hidden Markov Model written by and published by . This book was released on 2006 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt:
