Voice biometrics: technology, trust and security
Gespeichert in:
| Weitere beteiligte Personen: | , |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
London
The Institution of Engineering and Technology
2021
|
| Ausgabe: | First published |
| Schriftenreihe: | IET security series
12 |
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032123396&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | xxviii, 235 Seiten Illustrationen, Diagramme 234 mm |
| ISBN: | 9781785619007 |
Internformat
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Datensatz im Suchindex
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| adam_text | Contents List of figures List of tables Short biographies of the editors and authors Preface to Voice Biometrics About the editors 1 Introduction Carmen García-Mateo and Gérard Chollet Chapter 2 ֊ Fundamentals of voice biometrics: classical and machine learning approaches Chapter 3 - Voice biometrics: attacker’s perspective Chapter 4 - Voice biometrics: privacy in paralinguistic and extralinguistic tasks for health applications Chapter 5 - Voice privacy in biometrics: speaker de-identification Chapter 6 - Performance evaluation of voice biometrics solutions Chapter 7 - Voice biometrics: how the technology is standardized Chapter 8 - Voice biometrics: perspective from the industry Chapter 9 - Joining forces of voice and facial biometrics: a case study in the scope ofNISTSRE’19 Chapter 10 ֊ Voice biometrics: future trends and challenges ahead 2 Fundamentals of voice biometrics: classical and machine learning approaches Alicia Lozano-Diez, Joaquin Gonzalez-Rodriguez, Daniel Ramos, and Doroteo T Toledano 2.1 Introduction to speaker recognition systems 2.2 Metrics for system performance evaluation 2.2.1 ROC, DET and EER 2.2.2 Detection cost fimction 2.3 Text-independent speaker recognition 2.3.1 Classical acoustic approaches: GMM-UBM, i-vector and PLDA 2.3.2 DNN approaches 2.3.2.1 Basic concepts of neural networks 2.3.2.2 Some applications of DNNs to speech processing xi xv xvii xxvii xxix 1 1 2 3 3 3 4 4 4 5 7 7 9 9 10 11 11 14 14 17
vi Voice biometrics 2.4 2.5 2.3.3 DNNs for speaker recognition Text-dependent speaker recognition 2.4.1 Classification of systems and techniques 2.4.2 Databases and benchmarks Calibration of speaker recognition scores 2.5.1 Motivation: why to calibrate? 2.5.2 What is calibration? 2.5.3 Score-to-LR computation methods 2.5.3.1 Generative calibration models : fitting distributions to scores 2.5.3.2 Discriminative calibration models: transforming scores into LR values to optimize a cost fimction 2.5.4 Performance measurement of score-to-LR methods References 3 Voice biometrics: attacker’s perspective Priyanka Gupta and HemantA. Patil 17 21 21 22 23 23 25 27 28 28 30 31 39 Abstract 3.1 Introduction 3.2 Direct attacks 3.2.1 Spoofing attacks 3.2.2 Black box hardware attacks 3.2.3 Black box adversarial attacks 3.3 Indirect attacks 3.3.1 Attacks on corpora 3.3.2 Gray box hardware attacks 3.3.3 Gray box and white box adversarial attacks 3.4 Technological challenges 3.4.1 Extracting prosodic information 3.4.2 Enrolled users with malicious intent 3.4.3 Number of trials permitted on the ASV 3.4.4 Minuteness of the perturbation inadversarial attacks 3.4.5 Privacy preservation of speech and voice privacy 3.5 Conclusions and fiiture work Acknowledgments References 39 40 42 42 44 45 48 48 51 51 53 53 53 54 54 55 57 57 58 4 Voice biometrics: privacy in paralinguistic and extralinguistic tasks for health applications Francisco Teixeira, Alberto Abad, Isabel Trancoso, and Bhiksha Raj 67 4.1 4.2 Introduction Paralinguistic and extralinguistic tasks 4.2.1 Speech-affecting diseases 4.2.2 Methods
67 69 70 71
Contents vii 5 4.3 Cryptographic primitives and MPC for PPML 4.3.1 Homomorphic encryption 4.3.2 Oblivious transfer 4.3.3 Secure Multiparty Computation 4.3.3.1 Yao’s GCs protocol 4.3.3.2 Secret sharing 4.3.3.3 Security models 4.3.4 Distance-preserving hashing techniques Secure binary embeddings Secure modular hashing 4.4 PPML for paralinguistic and extralinguistic tasks 4.4.1 PPML for non-health-related tasks 4.4.2 PPML for health-related tasks 4.4.3 Private SVM+RBF for health-related tasks 4.4.3.1 Private RBF computation 4.4.3.2 Private SVM computation 4.4.3.3 Experimental setup 4.4.3.4 Model training and parameters 4.4.3.5 Private SVM implementation details 4.4.3.6 Classification results 4.4.3.7 Security and computationalperformance 4.5 Conclusions Acknowledgements References 72 72 73 73 74 75 76 77 77 78 78 78 79 80 81 81 82 83 83 84 84 86 86 86 Voice privacy in biometrics: speaker de-identification 93 Paula Lopez-Otero, Laura Docio-Fernandez, and Carmen García-Mateo 5.1 Introduction 5.2 How to evaluate speaker de-identification? 5.2.1 Subjective measures 5.2.2 Objective measures 5.3 Speaker de-identification techniques 5.3.1 Codebook mapping 5.3.2 Gaussian mixture model 5.3.3 Frequency warping 5.3.4 Deep learning techniques 5.4 Experiment definition 5.4.1 Piecewise definition of transformationfunctions 5.4.2 Pretrained transformation functions 5.4.3 De-identification based on DNNs 5.4.4 De-identification based on generative adversarial networks 5.5 Evaluation corpora 5.5.1 Evaluation metrics 93 95 95 97 98 99 100 101 102 102 103 104 106 107 108 109
viii Voice biometrics 5.6 Results and analysis 5.7 Conclusion Acknowledgements References 6 Performance evaluation of voice biometrics solutions 111 113 114 114 121 Jean-François Bonastre and Anthony Larcher 6.1 Introduction 6.2 Evaluating methods or technology 6.2.1 Existing benchmarking evaluations 6.2.2 Evaluation criteria 6.2.2.1 Evaluating a system producing hard decisions 6.2.2.2 Evaluating the goodness of verification scores 6.2.3 Statistical significance 6.2.4 Specific evaluation aspects 6.2.5 Evaluating related technologies 6.3 Bias in testing 6.4 Summary and propositions References 7 Voice biometrics: How the technology is standardized 121 123 124 125 125 127 129 129 130 131 132 133 139 Andreas Nautsch and Christoph Busch 7.1 Introduction 7.2 Biometrics standardization within ISO/IEC 7.2.1 Generalized system design 7.2.2 Harmonized biometric vocabulary 7.2.3 Performance testing and reporting 7.2.4 Presentation attack detection 7.2.5 Biometric information protection 7.3 Data interchange formats for passports and beyond 7.3.1 Motivation and background on encoding biometric data 7.3.2 Data interchange standard ISO/IEC 19794 7.3.3 Format structure 7.3.4 ISO/IEC 19794 Part 13: voice data 7.4 Discussion: de facto and ISO/IEC standards 7.4.1 On the general system design 7.4.2 Gap analysis: performance testing and reporting 7.4.3 Regarding implementations and data interchange formats 7.5 Conclusion Acknowledgements References 140 140 141 143 144 146 147 149 150 151 152 154 154 154 156 158 159 160 160
Contents 8 Voice biometrics: perspective from the industry ix 163 Marcel Kockmann, Kevin Farrell, Daniele Colibro, Claudio Vair, Anil Alexander, and Finnian Kelly 8.1 Automated password reset: an example of a commercial application using voice biometrics 8.1.1 Overview 8.1.2 Introduction 8.1.3 System architecture 8.1.4 Voice biometric system 8.1.5 Summary 8.2 Testing of commercial voice biometric systems 8.2.1 Introduction 8.2.1.1 Biometric testing 8.2.2 User analysis 8.2.3 Summary 8.3 Forensic speaker recognition 8.3.1 Introduction 8.3.2 Forensic speaker recognition and the strength of evidence 8.3.3 The forensic expert’s workflow 8.3.4 Technical challenges 8.3.4.1 Improving interpretability of scores 8.3.4.2 Score normalization 8.3.4.3 Score calibration 8.3.4.4 Condition adaptation 8.3.4.5 Dealing with multi-speaker recordings 8.3.5 Training-communication between system developers and end-users 8.3.6 Conclusions References 9 Joining forces of voice and facial biometrics: a case study in the scope of NIST SRE’19 164 164 164 165 167 169 169 169 170 172 174 175 175 176 176 178 180 180 181 181 182 182 182 183 186 Mohamed Amine Hmani, Aymen Mtibaa, and Dijana Petrovska Delacretaz 9.1 Introduction to the NIST SRE’ 19 challenge 9.1.1 The SRE’19 CTS challenge 9.1.2 The SRE’19 multimedia challenge 9.1.3 SRE ’ 19 evaluation metrics 9.2 TSP speaker verification system for the SRE’ 19 evaluation 9.2.1 A brief review of state of the art in speakerverification 9.2.2 TSP speaker verification common pipeline for the SRE’ 19 CTS and multimedia challenges 188 188 188 189 190 190 191
x Voice biometrics TDNN E-TDNN 9.2.3 TSP speaker verification system for the SRE’ 19 CTS challenge 9.2.4 TSP speaker verification system for the SRE’ 19 multimedia challenge 9.2.5 Results for TSP speaker verification systems on the SRE’19 CTS and multimedia challenges 9.2.6 Conclusions 9.3 TSP face recognition system for SRE’ 19 9.3.1 Survey of face recognition systems 9.3.2 TSP face recognition system pipeline 9.3.3 Databases used in the TSP face recognition system 9.3.4 Face preprocessing 9.3.5 Embedding extractor Initial version of the DNN architecture Final version of the DNN architecture 9.3.6 Conclusions 9.4 Audiovisual biometric system for the SRE’19 multimedia challenge 9.5 Conclusions and perspectives Acknowledgements References 10 Voice biometrics: future trends and challenges ahead Douglas Reynolds and Craig S. Greenberg 10.1 Applications 10.2 Privacy and security 10.3 Research References Index 191 192 192 193 194 197 197 197 200 201 202 205 205 205 208 208 212 214 214 219 219 220 221 223 227
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| id | DE-604.BV046713026 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T18:58:52Z |
| institution | BVB |
| isbn | 9781785619007 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032123396 |
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| owner | DE-29T DE-739 |
| owner_facet | DE-29T DE-739 |
| physical | xxviii, 235 Seiten Illustrationen, Diagramme 234 mm |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | The Institution of Engineering and Technology |
| record_format | marc |
| series | IET security series |
| series2 | IET security series IET book series in advances in biometrics |
| spellingShingle | Voice biometrics technology, trust and security IET security series Automatische Spracherkennung (DE-588)4003961-4 gnd Biometrie (DE-588)4124925-2 gnd |
| subject_GND | (DE-588)4003961-4 (DE-588)4124925-2 |
| title | Voice biometrics technology, trust and security |
| title_auth | Voice biometrics technology, trust and security |
| title_exact_search | Voice biometrics technology, trust and security |
| title_full | Voice biometrics technology, trust and security edited by Carmen García-Mateo and Gérard Chollet |
| title_fullStr | Voice biometrics technology, trust and security edited by Carmen García-Mateo and Gérard Chollet |
| title_full_unstemmed | Voice biometrics technology, trust and security edited by Carmen García-Mateo and Gérard Chollet |
| title_short | Voice biometrics |
| title_sort | voice biometrics technology trust and security |
| title_sub | technology, trust and security |
| topic | Automatische Spracherkennung (DE-588)4003961-4 gnd Biometrie (DE-588)4124925-2 gnd |
| topic_facet | Automatische Spracherkennung Biometrie |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=032123396&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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