Statistical Methods for Speech Recognition, Frederick Jelinek
Новое издание
Автор: Jelinek, Frederick Название: Statistical Methods For ISBN: 0262100665 ISBN-13(EAN): 9780262100663 Издательство: MIT Press Цена: 0.00 р. Наличие на складе: Невозможна поставка. Описание: This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques.
Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Dit-Yan Yeung; James T. Kwok; Ana Fred; Fabio Roli Название: Structural, Syntactic, and Statistical Pattern Recognition ISBN: 3540372369 ISBN-13(EAN): 9783540372363 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 11th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2006 and the 6th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2006, held in Hong Kong, August 2006 alongside the Conference on Pattern Recognition, ICPR 2006.
Автор: Bradley Efron and Trevor Hastie Название: Computer Age Statistical Inference ISBN: 1107149894 ISBN-13(EAN): 9781107149892 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.
Автор: Sakriani Sakti; Konstantin Markov; Satoshi Nakamur Название: Incorporating Knowledge Sources into Statistical Speech Recognition ISBN: 1441946764 ISBN-13(EAN): 9781441946768 Издательство: Springer Рейтинг: Цена: 19589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The authors address the problem of developing efficient automatic speech recognition systems that maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training manageable and improving speech recognition performance.
Автор: Uday Kamath; John Liu; James Whitaker Название: Deep Learning for NLP and Speech Recognition ISBN: 3030145956 ISBN-13(EAN): 9783030145958 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience.
Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book.
The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are:
Machine Learning, NLP, and Speech IntroductionThe first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning BasicsThe five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech
The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Автор: Niels da Vitoria Lobo; Takis Kasparis; Michael Geo Название: Structural, Syntactic, and Statistical Pattern Recognition ISBN: 3540896880 ISBN-13(EAN): 9783540896883 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Contains papers organized in topical sections on graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, and computer vision and biometrics.
Автор: Edwin R. Hancock; Richard C Wilson; Terry Windeatt Название: Structural, Syntactic, and Statistical Pattern Recognition ISBN: 3642149790 ISBN-13(EAN): 9783642149795 Издательство: Springer Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume in the Springer Lecture Notes in Computer Science (LNCS) series contains the papers presented at the S+SSPR 2010 Workshops, which was the seventh occasion that SPR and SSPR workshops have been held jointly. S+SSPR 2010 was organized by TC1 and TC2, Technical Committees of the International Association for Pattern Recognition(IAPR), andheld inCesme, Izmir, whichis a seaside resort on the Aegean coast of Turkey. The conference took place during August 18-20, 2010, only a few days before the 20th International Conference on Pattern Recognition (ICPR) which was held in Istanbul. The aim of the series of workshops is to create an international forum for the presentation of the latest results and exchange of ideas between researchers in the ?elds of statistical and structural pattern recognition. SPR 2010 and SSPR 2010 received a total of 99 paper submissions from many di?erent countries around the world, giving it a truly international perspective, as has been the case for previous S+SSPR workshops. This volume contains 70 accepted papers, 39 for oral and 31 for poster presentation. In addition to par- lel oral sessions for SPR and SSPR, there were two joint oral sessions of interest to both SPR and SSPR communities. Furthermore, to enhance the workshop experience, there were two joint panel sessions on "Structural Learning" and "Clustering," in which short author presentations were followed by discussion. Another innovation this year was the ?lming of the proceedings by Videol- tures.
Автор: Antonio Robles-Kelly; Marco Loog; Battista Biggio; Название: Structural, Syntactic, and Statistical Pattern Recognition ISBN: 3319490540 ISBN-13(EAN): 9783319490540 Издательство: Springer Рейтинг: Цена: 10342.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the Joint IAPR International Workshop on Structural Syntactic, and Statistical Pattern Recognition, S+SSPR 2016, consisting of the International Workshop on Structural and Syntactic Pattern Recognition SSPR, and the International Workshop on Statistical Techniques in Pattern Recognition, SPR.
Описание: This outstanding review of the literature on the core theoretical foundations of applied statistical pattern recognition defines a novel mode of pattern recognition and classification, based on independent component analysis mixture modeling (ICAMM).
Автор: Terry Caelli; Adnan Amin; Robert P.W. Duin; Mohame Название: Structural, Syntactic, and Statistical Pattern Recognition ISBN: 3540440119 ISBN-13(EAN): 9783540440116 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the proceedings of the 9th International Workshop on Structural and Syntactic Pattern Recognition and the 4th International Workshop on Statistical Techniques in Pattern Recognition held in Canada in 2002.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
