LEADER 05263nam 22007455 450 001 9910869157903321 005 20251225193708.0 010 $a9783031640377 010 $a3031640373 024 7 $a10.1007/978-3-031-64037-7 035 $a(CKB)32609883100041 035 $a(MiAaPQ)EBC31507669 035 $a(Au-PeEL)EBL31507669 035 $a(DE-He213)978-3-031-64037-7 035 $a(MiAaPQ)EBC31521830 035 $a(Au-PeEL)EBL31521830 035 $a(EXLCZ)9932609883100041 100 $a20240629d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInformation Technology in Disaster Risk Reduction $e8th IFIP WG 5.15 International Conference, ITDRR 2023, Tokyo, Japan, December 4?6, 2023, Revised Selected Papers /$fedited by Julie Dugdale, Terje Gjøsæter, Osamu Uchida 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2024. 215 $a1 online resource (288 pages) 225 1 $aIFIP Advances in Information and Communication Technology,$x1868-422X ;$v706 311 08$a9783031640360 311 08$a3031640365 320 $aIncludes bibliographical references and index. 327 $a -- Evacuation and Emergency Management. -- Risk and Control Assurance Framework for Emergency Management Projects. -- Digitalized Co-production of Emergency Response: Dispatch and on-site work by volunteer first responders. -- Proposing a Simple Method of Creating Tsunami Evacuation Simulations: Aiming to Empower Residents for Feasible Measures. -- Performance Evaluation of Flood Level Estimation Method using State-space Model with Time-series Monitoring Data. -- Situational Awareness. -- Snowed In and Cut Off: How a Norwegian Municipality Dealt with a Power Outage. -- Situational Disabilities in Emergency Management ? Validation of Realistic Scenarios for Training and Awareness-raising. -- TeamAware: Profile-based Interoperability Framework for First Responders. -- Social Media. -- Archiving Social Media Discussions in Time and Space: A focus on refugees from Middle East and related war conflicts during Jan 2015 ? Apr 2016. -- Location Extraction in Disaster Tweets with a Model Trained on Past Data: Diverse Analysis. -- Analysis of Japanese Tweets on the Russian Military Invasion of Ukraine Focusing on Frequently Used Words and Emotional Expressions. -- Information Systems. -- The Paradox Of Information Systems In Crisis: Walking The Tight Rope Between Rigidity & Flexibility. -- Digital Supply Chain Roles in the Power Industry. -- A Multi-modal Approach towards Public Alerting and Effective Communication in Disaster Scenarios: Implementation in the Indian Context. -- Geographic Information System (GIS). -- Identification of Undesignated Evacuation Sites Location by Mobile Spatial Statistics. -- Derivation of Evacuation Routes to Avoid Narrow Road Adopting Physarum Solver. -- Evaluation of Sentinel-1 GRD data with GEE for Floods mapping in Rubkona, South Sudan. -- Healthcare. -- A Novel Proof of Concept Forecasting Model for Pandemics ? A Case Study in New Zealand. -- Sensorized Maternal Health Interventions in Marginalized Communities: The Role of Surveillant Assemblages in Maintaining Compliance within Disaster-affected Healthcare Systems. 330 $aThis volume constitutes the refereed and revised post-conference proceedings of the 8th IFIP WG 5.15 International Conference on Information Technology in Disaster Risk Reduction, ITDRR 2023, held in Tokyo, Japan, during December 4-6, 2023. The 18 full papers were carefully reviewed and selected from 26 submissions. The papers were organized in topical sections as follows: Evacuation and Emergency Management; Situational Awareness; Social Media; Information Systems; Geographic Information System (GIS); and Healthcare. 410 0$aIFIP Advances in Information and Communication Technology,$x1868-422X ;$v706 606 $aApplication software 606 $aComputer engineering 606 $aComputer networks 606 $aCoding theory 606 $aInformation theory 606 $aSocial sciences$xData processing 606 $aComputer and Information Systems Applications 606 $aComputer Engineering and Networks 606 $aCoding and Information Theory 606 $aComputer Application in Social and Behavioral Sciences 615 0$aApplication software. 615 0$aComputer engineering. 615 0$aComputer networks. 615 0$aCoding theory. 615 0$aInformation theory. 615 0$aSocial sciences$xData processing. 615 14$aComputer and Information Systems Applications. 615 24$aComputer Engineering and Networks. 615 24$aCoding and Information Theory. 615 24$aComputer Application in Social and 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$aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aDistant speech recognition /$fMatthias Wolfel and John McDonough 205 $a1st ed. 210 $aChichester, West Sussex, U.K. $cWiley$dc2009 215 $a1 online resource (595 p.) 300 $aDescription based upon print version of record. 311 08$a9780470517048 311 08$a0470517042 320 $aIncludes bibliographical references and index. 327 $aForeword -- Preface -- 1 Introduction -- 1.1 Research and Applications in Academia and Industry -- 1.2 Challenges in Distant Speech Recognition -- 1.3 System Evaluation -- 1.4 Fields of Speech Recognition -- 1.5 Robust Perception -- 1.6 Organizations, Conferences and Journals -- 1.7 Useful Tools, Data Resources and Evaluation Campaigns -- 1.8 Organization of this Book -- 1.9 Principal Symbols used Throughout the Book -- 1.10 Units used Throughout the Book -- 2 Acoustics -- 2.1 Physical Aspect of Sound -- 2.2 Speech Signals -- 2.3 Human Perception of Sound -- 2.4 The Acoustic Environment -- 2.5 Recording Techniques and Sensor Configuration -- 2.6 Summary and Further Reading -- 2.7 Principal Symbols -- 3 Signal Processing and Filtering Techniques -- 3.1 Linear Time-Invariant Systems -- 3.2 The Discrete Fourier Transform -- 3.3 Short-Time Fourier Transform -- 3.4 Summary and Further Reading -- 3.5 Principal Symbols -- 4 Bayesian Filters -- 4.1 Sequential Bayesian Estimation -- 4.2 Wiener Filter -- 4.3 Kalman Filter and Variations -- 4.4 Particle Filters -- 4.5 Summary and Further Reading -- 4.6 Principal Symbols -- 5 Speech Feature Extraction -- 5.1 Short-Time Spectral Analysis -- 5.2 Perceptually Motivated Representation -- 5.3 Spectral Estimation and Analysis -- 5.4 Cepstral Processing -- 5.5 Comparison between Mel Frequency, Perceptual LP and warped MVDR Cepstral Coefficient Frontends -- 5.6 Feature Augmentation -- 5.7 Feature Reduction -- 5.8 Feature-Space Minimum Phone Error -- 5.9 Summary and Further Reading -- 5.10 Principal Symbols -- 6 Speech Feature Enhancement -- 6.1 Noise and Reverberation in Various Domains -- 6.2 Two Principal Approaches -- 6.3 Direct Speech Feature Enhancement -- 6.4 Schematics of Indirect Speech Feature Enhancement -- 6.5 Estimating Additive Distortion -- 6.6 Estimating Convolutional Distortion -- 6.7 Distortion Evolution -- 6.8 Distortion Evaluation -- 6.9 Distortion Compensation -- 6.10 Joint Estimation of Additive and Convolutional Distortions. 327 $a6.11 Observation Uncertainty -- 6.12 Summary and Further Reading -- 6.13 Principal Symbols -- 7 Search: Finding the Best Word Hypothesis -- 7.1 Fundamentals of Search -- 7.2 Weighted Finite-State Transducers -- 7.3 Knowledge Sources -- 7.4 Fast On-the-Fly Composition -- 7.5 Word and Lattice Combination -- 7.6 Summary and Further Reading -- 7.7 Principal Symbols -- 8 Hidden Markov Model Parameter Estimation -- 8.1 Maximum Likelihood Parameter Estimation -- 8.2 Discriminative Parameter Estimation -- 8.3 Summary and Further Reading -- 8.4 Principal Symbols -- 9 Feature and Model Transformation -- 9.1 Feature Transformation Techniques -- 9.2 Model Transformation Techniques -- 9.3 Acoustic Model Combination -- 9.4 Summary and Further Reading -- 9.5 Principal Symbols -- 10 Speaker Localization and Tracking -- 10.1 Conventional Techniques -- 10.2 Speaker Tracking with the Kalman Filter -- 10.3 Tracking Multiple Simultaneous Speakers -- 10.4 Audio-Visual Speaker Tracking -- 10.5 Speaker Tracking with the Particle Filter -- 10.6 Summary and Further Reading -- 10.7 Principal Symbols -- 11 Digital Filter Banks -- 11.1 Uniform Discrete Fourier Transform Filter Banks -- 11.2 Polyphase Implementation -- 11.3 Decimation and Expansion -- 11.4 Noble Identities -- 11.5 Nyquist(M) Filters -- 11.6 Filter Bank Design of De Haan et al -- 11.7 Filter Bank Design with the Nyquist(M) Criterion -- 11.8 Quality Assessment of Filter Bank Prototypes -- 11.9 Summary and Further Reading -- 11.10 Principal Symbols -- 12 Blind Source Separation -- 12.1 Channel Quality and Selection -- 12.2 Independent Component Analysis -- 12.3 BSS Algorithms based on Second-Order Statistics -- 12.4 Summary and Further Reading -- 12.5 Principal Symbols -- 13 Beamforming -- 13.1 Beamforming Fundamentals -- 13.2 Beamforming Performance Measures -- 13.3 Conventional Beamforming Algorithms -- 13.4 Recursive Algorithms -- 13.5 Nonconventional Beamforming Algorithms -- 13.6 Array Shape Calibration -- 13.7 Summary and Further Reading. 327 $a13.8 Principal Symbols -- 14 Hands On -- 14.1 Example Room Configurations -- 14.2 Automatic Speech Recognition Engines -- 14.3 Word Error Rate -- 14.4 Single-Channel Feature Enhancement Experiments -- 14.5 Acoustic Speaker-Tracking Experiments -- 14.6 Audio-Video Speaker-Tracking Experiments -- 14.7 Speaker-Tracking Performance vs Word Error Rate -- 14.8 Single-Speaker Beamforming Experiments -- 14.9 Speech Separation Experiments -- 14.10 Filter Bank Experiments -- 14.11 Summary and Further Reading -- Appendices -- A List of Abbreviations -- B Useful Background -- B.1 Discrete Cosine Transform -- B.2 Matrix Inversion Lemma -- B.3 Cholesky Decomposition -- B.4 Distance Measures -- B.5 Super-Gaussian Probability Density Functions -- B.6 Entropy -- B.7 Relative Entropy -- B.8 Transformation Law of Probabilities -- B.9 Cascade of Warping Stages -- B.10 Taylor Series -- B.11 Correlation and Covariance -- B.12 Bessel Functions -- B.13 Proof of the Nyquist / Shannon Sampling Theorem -- B.14 Proof of Equations (11.31 / 11.32) -- B.15 Givens Rotations -- B.16 Derivatives with Respect to Complex Vectors -- B.17 Perpendicular Projection Operators -- Bibliography -- Index. 330 $aA complete overview of distant automatic speech recognition The performance of conventional Automatic Speech Recognition (ASR) systems degrades dramatically as soon as the microphone is moved away from the mouth of the speaker. This is due to a broad variety of effects such as background noise, overlapping speech from other speakers, and reverberation. While traditional ASR systems underperform for speech captured with far-field sensors, there are a number of novel techniques within the recognition system as well as techniques developed in other areas of signal processing that can mitigate the deleterious effects of noise and reverberation, as well as separating speech from overlapping speakers. Distant Speech Recognitionpresents a contemporary and comprehensive description of both theoretic abstraction and practical issues inherent in the distant ASR problem. Key Features: *Covers the entire topic of distant ASR and offers practical solutions to overcome the problems related to it *Provides documentation and sample scripts to enable readers to construct state-of-the-art distant speech recognition systems *Gives relevant background information in acoustics and filter techniques, *Explains the extraction and enhancement of classification relevant speech features *Describes maximum likelihood as well as discriminative parameter estimation, and maximum likelihood normalization techniques *Discusses the use of multi-microphone configurations for speaker tracking and channel combination *Presents several applications of the methods and technologies described in this book *Accompanying website with open source software and tools to construct state-of-the-art distant speech recognition systems This reference will be an invaluable resource for researchers, developers, engineers and other professionals, as well as advanced students in speech technology, signal processing, acoustics, statistics and artificial intelligence fields. 606 $aAutomatic speech recognition 606 $aPattern perception 615 0$aAutomatic speech recognition. 615 0$aPattern perception. 676 $a006.4/54 700 $aWo?lfel$b Matthias$01117265 701 $aMcDonough$b John$g(John W.)$01671244 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910808716103321 996 $aDistant speech recognition$94186845 997 $aUNINA