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This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition;
Vergelijkbare producten zoals Machine Learning for Speaker Recognition
an important role in the performance of recognizer. Here we propose prosodic feature set for text dependent speaker recognition. Further we;
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author explains automatic speech recognition, and in Part IV biometrics recognition, face- and speaker-recognition. By Part V the author can then;
Vergelijkbare producten zoals The Application of Artificial Intelligence
author explains automatic speech recognition, and in Part IV biometrics recognition, face- and speaker-recognition. By Part V the author can then;
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characteristics. This work develops an integrated approach for speech and speaker recognition in order to gain space for self-learning opportunities;
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selected from 53 submissions. The papers are organized in topical sections on machine translation, speech and speaker recognition, machine learning;
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This book presents an overview of speaker recognition technologies with an emphasis on dealing with robustness issues. Firstly, the book;
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An emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks;
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An emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks;
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recognition. The respective chapters highlight the latest developments in vision-based machine perception and machine learning research for;
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recognition from speech, speech data mining, language resource and databases, machine learning for spoken dialog systems and educational and;
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recognition from speech, speech data mining, language resource and databases, machine learning for spoken dialog systems and educational and;
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address issues such as challenging issues in speech recognition and enhancement, speaker and language recognition, speech synthesis, corpus and;
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Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced;
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systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product;
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for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an;
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for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an;
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Learning (edited by S. Nayar and T. Poggio), this book is intended for researchers and students in machine vision and machine learning.;
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, face recognition, deep learning, time series recognition, image classification, and object detection.;
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to fraud, anomaly, and outlier detection Experiment with deep learning concepts and algorithms Write your own activity recognition model for;
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Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document;
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application of statistical machine learning algorithms for object tracking, activity modeling, and recognition. Developed from expert contributions;
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technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy-to-follow book;
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. They were organized in topical sections named: pattern recognition and machine learning; signal and image processing; computer vision and video;
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Speech recognition technology is being increasingly employed in human-machine interfaces. A remaining problem however is the robustness;
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Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing;
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submissions. They present and discuss new trends in deep and reinforcement learning, pattern recognition and classification for networks, machine;
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