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This book presents advances in speech and music in the domain of audio signal processing. The book begins with introductory chapters on the basics of speech and music, and then proceeds to computational aspects of speech and music, including music information retrieval and spoken language processing. The authors discuss the intersection in the field of computer science, musicology and speech analysis, and how the multifaceted nature of speech and music information processing requires unique algorithms, systems using sophisticated signal processing, and machine learning techniques that better extract useful information. The authors discuss how a deep understanding of both speech and music in terms of perception, emotion, mood, gesture and cognition is essential for successful application. Also discussed is the overwhelming amount of data that has been generated across the world that requires efficient processing for better maintenance, retrieval, indexing and querying and how machine learning and artificial intelligence are most suited for these computational tasks. The book provides both technological knowledge and a comprehensive treatment of essential topics in speech and music processing. Presents comprehensive coverage of the interdisciplinary aspects of speech and music processing; Offer detailed technological insights and a deep understanding of speech and music processing applications by considering both theory and practice in the relevant topics; Topics include music information retrieval and spoken language processing that takes into account perception, emotion, mood, and cognition.

Music --- Speech --- Speech synthesis. --- Data processing. --- Synthetic speech --- Computer input-output equipment --- Speech processing systems --- Talking --- Language and languages --- Oral communication --- Phonetics --- Voice --- Synthesis

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Online social networks. --- Electronic social networks --- Social networking Web sites --- Virtual communities --- Social media --- Social networks --- Sociotechnical systems --- Web sites --- Communities, Online (Online social networks) --- Communities, Virtual (Online social networks) --- Online communities (Online social networks)

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Graph algorithms. --- Graph databases.

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This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help of computing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression. .

Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- neuronale netwerken --- fuzzy logic --- cybernetica --- datamining --- medische informatica --- KI (kunstmatige intelligentie) --- data acquisition --- AI (artificiële intelligentie)

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Swarm Intelligence (SI) has grown significantly, both from the perspective of algorithmic development and applications covering almost all disciplines science and technology. This book emphasizes the studies of existing SI techniques, their variants and applications. The book also contains reviews of new developments in SI techniques and hybridizations. Algorithm specific studies covering basic introduction and analysis of key components of these algorithms, such as convergence, balance of solution accuracy, computational costs, tuning and control of parameters. Application specific studies incorporating the ways of designing objective functions, solution representation and constraint handling. The book also includes studies on application domain specific adaptations in the SI techniques. The book will be beneficial for academicians and researchers from various disciplines of engineering and science working in applications of SI and other optimization problems. .

Artificial intelligence. Robotics. Simulation. Graphics --- neuronale netwerken --- fuzzy logic --- cybernetica --- KI (kunstmatige intelligentie) --- AI (artificiële intelligentie)