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001453784 001__ 1453784
001453784 003__ OCoLC
001453784 005__ 20230314003444.0
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001453784 019__ $$a1356793645$$a1356796415$$a1357016462
001453784 020__ $$a9783031184444$$qelectronic book
001453784 020__ $$a3031184440$$qelectronic book
001453784 020__ $$z9783031184437
001453784 020__ $$z3031184432
001453784 0247_ $$a10.1007/978-3-031-18444-4$$2doi
001453784 035__ $$aSP(OCoLC)1357149725
001453784 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dYDX$$dEBLCP$$dYDX$$dOCLCQ$$dUKAHL
001453784 049__ $$aISEA
001453784 050_4 $$aTK7882.S65$$bA38 2022
001453784 08204 $$a006.4/54$$223/eng/20230109
001453784 24500 $$aAdvances in speech and music technology :$$bcomputational aspects and applications /$$cAnupam Biswas, Emile Wennekes, Alicja Wieczorkowska, Rabul Hussain Laskar, editors.
001453784 264_1 $$aCham :$$bSpringer,$$c2022.
001453784 300__ $$a1 online resource (1 volume) :$$billustrations
001453784 336__ $$atext$$btxt$$2rdacontent
001453784 337__ $$acomputer$$bc$$2rdamedia
001453784 338__ $$aonline resource$$bcr$$2rdacarrier
001453784 4901_ $$aSignals and communication technology
001453784 504__ $$aIncludes bibliographical references and index.
001453784 5050_ $$aState-of-the-Art -- A comprehensive review on Speaker Recognition -- Music Composition with Deep Learning: A Review -- Music Recommendation Systems: Overview and Challenges -- Music Recommender Systems: A Review Centered on Biases -- Computational Approaches for Indian Classical Music: A Comprehensive Review -- Machine Learning -- A Study on Effectiveness of Deep Neural Networks for Speech Signal Enhancement in Comparison with Wiener Filtering Technique -- Video Soundtrack Evaluation with Machine Learning: Data Availability, Feature Extraction and Classification -- Deep Learning Approach to Joint Identification of Instrument, Shruthi and Raga for Indian Classical Music -- Comparison of Convolutional Neural Networks and K-Nearest Neighbours for Music Instrument Recognition -- Emotion Recognition in Music using Deep Neural Networks -- Perception, Health and Emotion -- Music to Ears in Hearing Impaired-Signal Processing Advancements in Hearing Amplification Devices -- Music Therapy - A Best Way to Solve Anxiety and Depression in Diabetes Mellitus Patients -- Music and Stress During Covid-19 Lockdown: Influence of Locus of Control and Coping Styles on Musical Preferences -- Biophysics of Brain Plasticity and Its Correlation to Music Learning -- Dealing with Emotional Speech and Text: A Special Focus on Bengali Language -- Case Studies -- Duplicate Detection for Digital Audio Archive Management: Two Case Studies -- Section Order, Refrain Perception, and the Interpretation of a Songs Meaning -- Musical Influence on Visual Aesthetics: An Exploration on Intermediality using Audience Response, Feature and Fractal Analysis -- Influence of Musical Acoustics on Graphic Design: An Exploration with Indian Classical Music Album Cover Design -- A Fractal Approach to Characterize Emotions in Audio and Visual Domain: A Study on Cross-Modal Interaction -- Inharmonic Frequency Analysis of Tabla Strokes in North Indian Classical Music.
001453784 506__ $$aAccess limited to authorized users.
001453784 520__ $$aThis book presents advances in speech and music in the domain of audio signal processing. The book begins with introductory chapters on the basics of speech and music, and then proceeds to computational aspects of speech and music, including music information retrieval and spoken language processing. The authors discuss the intersection in the field of computer science, musicology and speech analysis, and how the multifaceted nature of speech and music information processing requires unique algorithms, systems using sophisticated signal processing, and machine learning techniques that better extract useful information. The authors discuss how a deep understanding of both speech and music in terms of perception, emotion, mood, gesture and cognition is essential for successful application. Also discussed is the overwhelming amount of data that has been generated across the world that requires efficient processing for better maintenance, retrieval, indexing and querying and how machine learning and artificial intelligence are most suited for these computational tasks. The book provides both technological knowledge and a comprehensive treatment of essential topics in speech and music processing. Presents comprehensive coverage of the interdisciplinary aspects of speech and music processing; Offer detailed technological insights and a deep understanding of speech and music processing applications by considering both theory and practice in the relevant topics; Topics include music information retrieval and spoken language processing that takes into account perception, emotion, mood, and cognition.
001453784 650_0 $$aSpeech processing systems.
001453784 650_0 $$aMusic$$xData processing.
001453784 650_0 $$aComputer music.
001453784 655_0 $$aElectronic books.
001453784 7001_ $$aBiswas, Anupam,$$eeditor.
001453784 7001_ $$aWennekes, Emile,$$d1963-$$eeditor.$$1https://isni.org/isni/0000000109595969
001453784 7001_ $$aWieczorkowska, Alicja A.,$$eeditor.$$1https://isni.org/isni/0000000102493417
001453784 7001_ $$aLaskar, Rabul Hussain,$$eeditor.
001453784 77608 $$iPrint version:$$tAdvances in speech and music technology.$$dCham : Springer, 2022$$z9783031184437$$w(OCoLC)1348994141
001453784 830_0 $$aSignals and communication technology.
001453784 852__ $$bebk
001453784 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-18444-4$$zOnline Access$$91397441.1
001453784 909CO $$ooai:library.usi.edu:1453784$$pGLOBAL_SET
001453784 980__ $$aBIB
001453784 980__ $$aEBOOK
001453784 982__ $$aEbook
001453784 983__ $$aOnline
001453784 994__ $$a92$$bISE