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001444127 001__ 1444127
001444127 003__ OCoLC
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001444127 019__ $$a1294345097$$a1294428662$$a1294453547$$a1296667039
001444127 020__ $$a9783030957117$$q(electronic bk.)
001444127 020__ $$a303095711X$$q(electronic bk.)
001444127 020__ $$z9783030957100$$q(print)
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001444127 0247_ $$a10.1007/978-3-030-95711-7$$2doi
001444127 035__ $$aSP(OCoLC)1295094080
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001444127 049__ $$aISEA
001444127 050_4 $$aQ335$$b.I58 2021eb
001444127 08204 $$a006.3$$223
001444127 1112_ $$aInternational Conference on Artificial Intelligence and Speech Technology$$n(3rd :$$d2021 :$$cDelhi, India)
001444127 24510 $$aArtificial intelligence and speech technology :$$bthird International Conference, AIST 2021, Delhi, India, November 12-13, 2021, Revised selected papers /$$cAmita Dev, S. S. Agrawal, Arun Sharma (eds.).
001444127 2463_ $$aAIST 2021
001444127 264_1 $$aCham, Switzerland :$$bSpringer,$$c2022.
001444127 300__ $$a1 online resource (xvii, 676 pages) :$$billustrations (some color).
001444127 336__ $$atext$$btxt$$2rdacontent
001444127 337__ $$acomputer$$bc$$2rdamedia
001444127 338__ $$aonline resource$$bcr$$2rdacarrier
001444127 347__ $$atext file$$bPDF$$2rda
001444127 4901_ $$aCommunications in computer and information science,$$x1865-0937 ;$$v1546
001444127 500__ $$aIncludes author index.
001444127 5050_ $$aIntro -- Preface -- Organization -- Contents -- Speech and Natural language Processing -- A Critical Insight into Automatic Visual Speech Recognition System -- 1 Introduction -- 2 Related Work -- 3 Applications of Speech Recognition -- 3.1 In the Workplace -- 3.2 In Banking -- 3.3 In Marketing -- 4 Convolutional Neural Network -- 5 Kaldi Toolkit -- 6 Proposed Methodology -- 6.1 Combining Residual Networks with LSTMs for Lipreading -- 6.2 Deep Word Embedding -- 6.3 Lrw-1000 -- 6.4 Marathi Language Vowels and Consonants -- 7 Features Extraction -- 7.1 Visual Preprocessing
001444127 5058_ $$a7.2 Region of Interest (ROI) Extraction -- 7.3 Visual Feature Extraction -- 8 Conclusion -- References -- Speaker Independent Accent Based Speech Recognition for Malayalam Isolated Words: An LSTM-RNN Approach -- 1 Introduction -- 2 Related Work -- 2.1 Accent Based Speech Recognition Using RNN in Literature -- 3 Proposed Methodology and Design -- 3.1 The Blueprint of the Model -- 3.2 Dataset -- 3.3 Feature Extraction -- 3.4 Model Building Using LSTMRNN -- 4 Result and Discussion -- 5 The Performance Evaluation Metrics -- 6 Conclusion -- References
001444127 5058_ $$aA Review on Speech Synthesis Based on Machine Learning -- 1 Introduction -- 2 Literature Survey -- 2.1 Support Vector Machine (SVM) Based Speech Enhancement Systems -- 2.2 Neural Network Based Text to Speech Synthesis Technique -- 2.3 Multi -level Speech Synthesis Based Gaussian Mixture Modeling -- 2.4 Speech Synthesis Using Generative Adversarial Network -- 2.5 DNN Based Speech Synthesis Technique -- 2.6 Speech Synthesis Techniques Based on HMM -- 2.7 Multilingual Text to Speech Synthesis -- 3 Comparative Analysis and Discussion of Speech Synthesis Framework -- 4 Conclusion -- References
001444127 5058_ $$aHindi Phoneme Recognition -- A Review -- 1 Introduction -- 2 Related Work -- 3 Hindi Language -- 4 Feature Extraction Methods -- 5 Classification Methods -- 6 Results and Analysis -- 7 Conclusion -- References -- Comparison of Modelling ASR System with Different Features Extraction Methods Using Sequential Model -- 1 Introduction -- 2 Related Work -- 3 Experiment Conducted -- 4 Results and Outcomes -- 5 Conclusion -- References -- Latest Trends in Deep Learning for Automatic Speech Recognition System -- 1 Introduction -- 2 Deep Learning -- 2.1 Auto-encoder -- 2.2 Convolutional Neural Network
001444127 5058_ $$a2.3 Generative Adversarial Network -- 2.4 Restricted Boltzmann Machine -- 2.5 Deep Belief Network -- 2.6 Deep Stacking Network -- 2.7 Long Short-Term Memory -- 3 Related Work -- 4 Comparison Table -- 5 Characteristics of Deep Learning -- 6 Motivation for Using Deep Learning -- 7 Machine Learning vs. Deep Learning -- 8 Challenges of Deep Learning -- 9 Conclusion and Future Aspects -- References -- Deep Learning Approaches for Speech Analysis: A Critical Insight -- 1 Introduction -- 2 Related Work -- 3 Proposed Work -- 4 Results and Discussion -- 5 Conclusion -- References
001444127 506__ $$aAccess limited to authorized users.
001444127 520__ $$aThis volume constitutes selected papers presented at the Third International Conference on Artificial Intelligence and Speech Technology, AIST 2021, held in Delhi, India, in November 2021. The 36 full papers and 18 short papers presented were thoroughly reviewed and selected from the 178 submissions. They provide a discussion on application of Artificial Intelligence tools in speech analysis, representation and models, spoken language recognition and understanding, affective speech recognition, interpretation and synthesis, speech interface design and human factors engineering, speech emotion recognition technologies, audio-visual speech processing and several others.
001444127 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed February 4, 2022).
001444127 650_0 $$aArtificial intelligence$$vCongresses.
001444127 650_0 $$aSpeech processing systems$$vCongresses.
001444127 650_6 $$aIntelligence artificielle$$vCongrès.
001444127 650_6 $$aTraitement automatique de la parole$$vCongrès.
001444127 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001444127 655_0 $$aElectronic books.
001444127 7001_ $$aDev, Amita,$$eeditor.
001444127 7001_ $$aAgrawal, S. S.$$eeditor.
001444127 7001_ $$aSharma, Arun,$$eeditor.$$0(orcid)0000-0002-9404-4519$$1https://orcid.org/0000-0002-9404-4519
001444127 77608 $$iPrint version: $$z3030957101$$z9783030957100$$w(OCoLC)1290430301
001444127 830_0 $$aCommunications in computer and information science ;$$v1546.$$x1865-0937
001444127 852__ $$bebk
001444127 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-95711-7$$zOnline Access$$91397441.1
001444127 909CO $$ooai:library.usi.edu:1444127$$pGLOBAL_SET
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001444127 980__ $$aEBOOK
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