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Author : Dave von Hausen
Publisher :
ISBN 13 :
Total Pages : 92 pages
Book Rating : 4.:/5 (277 download)
Download or read book Speech Recognition Using Hidden Markov Models in Noisy Environments written by Dave von Hausen and published by . This book was released on 1992 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Francisco Javier Hernando Pericás
Publisher :
ISBN 13 :
Total Pages : 10 pages
Book Rating : 4.:/5 (83 download)
Download or read book Speech Recognition in Noisy Environments Using Discrete Hidden Markov Models written by Francisco Javier Hernando Pericás and published by . This book was released on 1994 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Mark Gales
Publisher : Now Publishers Inc
ISBN 13 : 1601981201
Total Pages : 125 pages
Book Rating : 4.6/5 (19 download)
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.
Author : Francisco Javier Hernando Pericás
Publisher :
ISBN 13 :
Total Pages : 10 pages
Book Rating : 4.:/5 (83 download)
Download or read book HMM-Based Speech Recognition in Noisy Car Environments Usingdiscrete Hidden Markov Models written by Francisco Javier Hernando Pericás and published by . This book was released on 1994 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : K. Sreenivasa Rao
Publisher : Springer Science & Business Media
ISBN 13 : 3319031163
Total Pages : 129 pages
Book Rating : 4.3/5 (19 download)
Download or read book Speech Processing in Mobile Environments written by K. Sreenivasa Rao and published by Springer Science & Business Media. This book was released on 2014-01-28 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on speech processing in the presence of low-bit rate coding and varying background environments. The methods presented in the book exploit the speech events which are robust in noisy environments. Accurate estimation of these crucial events will be useful for carrying out various speech tasks such as speech recognition, speaker recognition and speech rate modification in mobile environments. The authors provide insights into designing and developing robust methods to process the speech in mobile environments. Covering temporal and spectral enhancement methods to minimize the effect of noise and examining methods and models on speech and speaker recognition applications in mobile environments.
Author : Emdad Rahman Khan
Publisher :
ISBN 13 :
Total Pages : 288 pages
Book Rating : 4.:/5 (63 download)
Download or read book Robust Speech Recognition Using a Noise Rejection Approach written by Emdad Rahman Khan and published by . This book was released on 1998 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Dorothea Kolossa
Publisher : Springer Science & Business Media
ISBN 13 : 3642213170
Total Pages : 387 pages
Book Rating : 4.6/5 (422 download)
Download or read book Robust Speech Recognition of Uncertain or Missing Data written by Dorothea Kolossa and published by Springer Science & Business Media. This book was released on 2011-07-14 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.
Author :
Publisher :
ISBN 13 :
Total Pages : 282 pages
Book Rating : 4.:/5 (94 download)
Download or read book Improved Speech Recognition Through the Use of Noise-compensated Hidden Markov Models written by and published by . This book was released on 1995 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Linear Dynamic Model for Continuous Speech Recognition written by and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past decades, statistics-based hidden Markov models (HMMs) have become the predominant approach to speech recognition. Under this framework, the speech signal is modeled as a piecewise stationary signal (typically over an interval of 10 milliseconds). Speech features are assumed to be temporally uncorrelated. While these simplifications have enabled tremendous advances in speech processing systems, for the past several years progress on the core statistical models has stagnated. Since machine performance still significantly lags human performance, especially in noisy environments, researchers have been looking beyond the traditional HMM approach. Recent theoretical and experimental studies suggest that exploiting frame-to-frame correlations in a speech signal further improves the performance of ASR systems. This is typically accomplished by developing an acoustic model which includes higher order statistics or trajectories. Linear Dynamic Models (LDMs) have generated significant interest in recent years due to their ability to model higher order statistics. LDMs use a state space-like formulation that explicitly models the evolution of hidden states using an autoregressive process. This smoothed trajectory model allows the system to better track the speech dynamics in noisy environments. In this dissertation, we develop a hybrid HMM/LDM speech recognizer that effectively integrates these two powerful technologies. This hybrid system is capable of handling large recognition tasks, is robust to noise-corrupted speech data and mitigates the ill-effects of mismatched training and evaluation conditions. This two-pass system leverages the temporal modeling and N-best list generation capabilities of the traditional HMM architecture in a first pass analysis. In the second pass, candidate sentence hypotheses are re-ranked using a phone-based LDM model. The Wall Street Journal (WSJ0) derived Aurora-4 large vocabulary corpus was chosen as the training and evaluation dataset. This corpus is a well-established LVCSR benchmark with six different noisy conditions. The implementation and evaluation of the proposed hybrid HMM/LDM speech recognizer is the major contribution of this dissertation.
Author : Clifford Joseph Weinstein
Publisher :
ISBN 13 :
Total Pages : 36 pages
Book Rating : 4.:/5 (212 download)
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).
Author : A. Acero
Publisher : Springer Science & Business Media
ISBN 13 : 1461531225
Total Pages : 197 pages
Book Rating : 4.4/5 (615 download)
Download or read book Acoustical and Environmental Robustness in Automatic Speech Recognition written by A. Acero and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: The need for automatic speech recognition systems to be robust with respect to changes in their acoustical environment has become more widely appreciated in recent years, as more systems are finding their way into practical applications. Although the issue of environmental robustness has received only a small fraction of the attention devoted to speaker independence, even speech recognition systems that are designed to be speaker independent frequently perform very poorly when they are tested using a different type of microphone or acoustical environment from the one with which they were trained. The use of microphones other than a "close talking" headset also tends to severely degrade speech recognition -performance. Even in relatively quiet office environments, speech is degraded by additive noise from fans, slamming doors, and other conversations, as well as by the effects of unknown linear filtering arising reverberation from surface reflections in a room, or spectral shaping by microphones or the vocal tracts of individual speakers. Speech-recognition systems designed for long-distance telephone lines, or applications deployed in more adverse acoustical environments such as motor vehicles, factory floors, oroutdoors demand far greaterdegrees ofenvironmental robustness. There are several different ways of building acoustical robustness into speech recognition systems. Arrays of microphones can be used to develop a directionally-sensitive system that resists intelference from competing talkers and other noise sources that are spatially separated from the source of the desired speech signal.
Author : Michael Mason
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (225 download)
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:
Author : France Mihelič
Publisher : BoD – Books on Demand
ISBN 13 : 953761929X
Total Pages : 580 pages
Book Rating : 4.5/5 (376 download)
Download or read book Speech Recognition written by France Mihelič and published by BoD – Books on Demand. This book was released on 2008-11-01 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes.
Download or read book Speech recognition in noise environment written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Este trabalho apresenta um estudo comparativo de três técnicas de melhoria das taxas de reconhecimento de voz em ambiente adverso, a saber: Normalização da Média Cepestral (CMN), Subtração Espectral e Regressão Linear no Sentido da Máxima Verossimilhança (MLLR), aplicadas isoladamente e em concomitância, duas a duas. Os testes são realizados usando um sistema simples: reconhecimento de palavras isoladas (dígitos de zero a nove, e meia), modo dependente do locutor, modelos ocultos de Markov do tipo contínuo, e vetores de atributos com doze coeficientes cepestrais derivados da análise de predição linear. São adotados três tipos de ruído (gaussiano branco, falatório e de fábrica) em nove razões sinal-ruído diferentes. Os resultados experimentais demonstram que o emprego isolado das técnicas de reconhecimento robusto é, em geral, vantajoso, pois nas diversas razões sinal-ruído para as quais os testes são efetuados, quando as taxas de reconhecimento não sofrem um acréscimo, mantém-se as mesmas obtidas quando não se aplica nenhum método de aumento da robustez. Analisando-se comparativamente as implementações isoladas e simultânea das técnicas, constata-se que a simultânea nem sempre é atraente, dependendo da dupla empregada. Apresentam-se, ainda, os resultados decorrentes do uso de modelos ruidosos, observando-se que, embora sejam inegavelmente melhores, sua utilização é inviável na prática. Das técnicas implementadas, a que representa resultados mais próximos ao emprego de modelos ruidosos é a MLLR, seguida pela CMN, e por último pela Subtração Espectral. Estas últimas, embora percam em desempenho para a primeira, apresentam como vantagem a simplicidade e a generalidade. No que concerne as técnicas usadas concomitantemente, a dupla Subtração Espectral e MLLR é a considerada de melhor performance, pois mostra-se conveniente em relação ao emprego isolado de ambos os métodos, o que nem sempre ocorre com o uso de outras combinações das técnicas individuais.
Author : Aleem Mushtaq
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (866 download)
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.
Author : Adam Wieworka
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (594 download)
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:
Author : Yves Normandin
Publisher : National Library of Canada = Bibliothèque nationale du Canada
ISBN 13 :
Total Pages : 180 pages
Book Rating : 4.:/5 (318 download)
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:
