A Computational Model of Auditory Pattern Recognition PDF Download

Author: Sven E. Anderson
Publisher:
ISBN:
Category :
Languages : en
Pages : 340

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Author: Steven Greenberg
Publisher: John Wiley & Sons
ISBN: 9789051994575
Category : Computers
Languages : en
Pages : 378

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NoA proven approach that reactivates knowledge, develops skills, and helps your students spiral upward toward a higher level of language! DU TAC AU TAC teaches students how to effectively and successfully manage conversations, moving from the controlled to the spontaneous as the book progresses. Bragger and Rice's proven communicative strategies help students reactivate and strengthen and build on what they already know, enabling them to spiral upward toward a higher level of language needed in more sophisticated interactions and discussions including literary and cultural.

Author: Keith Ponting
Publisher: Springer
ISBN:
Category : Comics & Graphic Novels
Languages : en
Pages : 490

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Proceedings of the NATO Advanced Study Institute on Computational Models of Speech Pattern Processing, held in St. Helier, Jersey, UK, July 7-18, 1997

Author: Martin Cooke
Publisher: Cambridge University Press
ISBN: 9780521619387
Category : Computers
Languages : en
Pages : 142

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Book Description
We are surrounded by noise; to separate the signals we want to hear from those we do not we have developed various strategies. Giving computers similar abilities would help develop devices such as intelligent hearing aids. This book reviews new and recent work on the modelling of auditory processes.

Author: David J. Getty
Publisher: Routledge
ISBN: 9781138692121
Category : Auditory perception
Languages : en
Pages : 0

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Book Description
Acoustic Characteristics of Sounds in the Ocean -- Pattern-Recognition Overview -- References -- PART IV: MULTIDIMENSIONAL PERCEPTUAL SPACES -- 10. Multidimensional Perception Spaces: Similarity Judgment and Identification -- The Perceptual Space -- Similarity Judgment -- Identification -- Prediction of Confusion Matrices: Illustrative Results -- References -- 11. Feature Selection in Auditory Perception -- Feature Selection Processes -- Stimulus Effects in Feature Extraction -- Task Effects in Feature Extraction -- Conclusion -- References -- 12. Auditory Perception: Recommendations for a Computer Assisted Experimental Paradigm -- Experimental Design Considerations -- Design Objectives -- Some Experimental Design Details -- Conclusions -- References -- Author Index -- Subject Index

Author: Keith Dana Martin
Publisher:
ISBN:
Category :
Languages : en
Pages : 172

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Author: Bernd Michaelis
Publisher: Springer
ISBN: 3540452435
Category : Computers
Languages : en
Pages : 638

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This book constitutes the refereed proceedings of the 25th Symposium of the German Association for Pattern Recognition, DAGM 2003, held in Magdeburg, Germany in September 2003. The 74 revised papers presented were carefully reviewed and selected from more than 140 submissions. The papers address all current issues in pattern recognition and are organized in sections on image analyses, callibration and 3D shape, recognition, motion, biomedical applications, and applications.

Author: Deliang Wang
Publisher: Wiley-IEEE Press
ISBN:
Category : Medical
Languages : en
Pages : 432

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Provides a comprehensive and coherent account of the state of the art in CASA, in terms of the underlying principles, the algorithms and system architectures that are employed, and the potential applications of this exciting new technology.

Author: Ray Meddis
Publisher: Springer Science & Business Media
ISBN: 1441959343
Category : Medical
Languages : en
Pages : 290

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Book Description
The Springer Handbook of Auditory Research presents a series of comprehensive and synthetic reviews of the fundamental topics in modern auditory research. The v- umes are aimed at all individuals with interests in hearing research including advanced graduate students, post-doctoral researchers, and clinical investigators. The volumes are intended to introduce new investigators to important aspects of hearing science and to help established investigators to better understand the fundamental theories and data in fields of hearing that they may not normally follow closely. Each volume presents a particular topic comprehensively, and each serves as a synthetic overview and guide to the literature. As such, the chapters present neither exhaustive data reviews nor original research that has not yet appeared in pe- reviewed journals. The volumes focus on topics that have developed a solid data and conceptual foundation rather than on those for which a literature is only beg- ning to develop. New research areas will be covered on a timely basis in the series as they begin to mature.

Author: Woojay Jeon
Publisher:
ISBN:
Category :
Languages : en
Pages : 124

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Book Description
It is well known that machines perform far worse than humans in recognizing speech and audio, especially in noisy environments. One method of addressing this issue of robustness is to study physiological models of the human auditory system and to adopt some of its characteristics in computers. As a first step in studying the potential benefits of an elaborate computational model of the primary auditory cortex (A1) in the central auditory system, we qualitatively and quantitatively validate the model under existing speech processing recognition methodology. Next, we develop new insights and ideas on how to interpret the model, and reveal some of the advantages of its dimension-expansion that may be potentially used to improve existing speech processing and recognition methods. This is done by statistically analyzing the neural responses to various classes of speech signals and forming empirical conjectures on how cognitive information is encoded in a category-dependent manner. We also establish a theoretical framework that shows how noise and signal can be separated in the dimension-expanded cortical space. Finally, we develop new feature selection and pattern recognition methods to exploit the category-dependent encoding of noise-robust cognitive information in the cortical response. Category-dependent features are proposed as features that "specialize" in discriminating specific sets of classes, and as a natural way of incorporating them into a Bayesian decision framework, we propose methods to construct hierarchical classifiers that perform decisions in a two-stage process. Phoneme classification tasks using the TIMIT speech database are performed to quantitatively validate all developments in this work, and the results encourage future work in exploiting high-dimensional data with category(or class)-dependent features for improved classification or detection.