Distant speech recognition:
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Chichester
Wiley
2009
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| Ausgabe: | 1. publ. |
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| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIX, 573 S. graph. Darst. |
| ISBN: | 9780470517048 |
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Datensatz im Suchindex
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| adam_text | DISTANT SPEECH RECOGNITION MATTHIAS WOLFEL UNIVERSITAT KARLSRUHE (TH),
GERMANY AND JOHN MCDONOUGH UNIVERSITAT DES SAARLANDES, GERMANY WILEY A
JOHN WILEY AND SONS, LTD., PUBLICATION CONTENTS FOREWORD XIII PREFACE
XVII 1 INTRODUCTION 1 1.1 RESEARCH AND APPLICATIONS IN ACADEMIA AND
INDUSTRY 1 1.1.1 INTELLIGENT HOME AND OFFICE ENVIRONMENTS 2 1.1.2
HUMANOID ROBOTS 3 1.1.3 AUTOMOBILES 4 1.1.4 SPEECH-TO-SPEECH TRANSLATION
6 1.2 CHALLENGES IN DISTANT SPEECH RECOGNITION _ 7 1.3 SYSTEM EVALUATION
9 1.4 FIELDS OF SPEECH RECOGNITION 10 1.5 ROBUST PERCEPTION 12 1.5.1 A
PRIORI KNOWLEDGE 12 1.5.2 PHONEMIC RESTORATION AND RELIABILITY 12 1.5.3
BINAURAL MASKING LEVEL DIFFERENCE 14 1.5.4 MULTI-MICROPHONE PROCESSING
14 1.5.5 MULTIPLE SOURCES BY DIFFERENT MODALITIES 15 1.6 ORGANIZATIONS,
CONFERENCES AND JOURNALS 16 1.7 USEFUL TOOLS, DATA RESOURCES AND
EVALUATION CAMPAIGNS 18 1.8 ORGANIZATION OF THIS BOOK 18 1.9 PRINCIPAL
SYMBOLS USED THROUGHOUT THE BOOK 23 1.10 UNITS USED THROUGHOUT THE BOOK
25 2 ACOUSTICS 27 2.1 PHYSICAL ASPECT OF SOUND 27 2.7.7 PROPAGATION OF
SOUND IN AIR 28 2.7.2 THE SPEED OF SOUND 29 2.1.3 WAVE EQUATION AND
VELOCITY POTENTIAL 29 2.1.4 SOUND INTENSITY AND ACOUSTIC POWER 31 2.7.5
REFLECTIONS OF PLANE WAVES 32 2.7.6 REFLECTIONS OF SPHERICAL WAVES 33 VI
CONTENTS 2.2 SPEECH SIGNALS 34 2.2.7 PRODUCTION OF SPEECH SIGNALS 34
2.2.2 UNITS OF SPEECH SIGNALS 36 2.2.3 CATEGORIES OF SPEECH SIGNALS 39
2.2.4 STATISTICS OF SPEECH SIGNALS 39 2.3 HUMAN PERCEPTION OF SOUND 41
2.3.7 PHASE INSENSITIVITY 42 2.3.2 FREQUENCY RANGE AND SPECTRAL
RESOLUTION 42 2.3.3 HEARING LEVEL AND SPEECH INTENSITY 42 2.3.4 MASKING
44 2.3.5 BINAURAL HEARING 45 2.3.6 WEIGHTING CURVES 45 2.3.7 VIRTUAL
PITCH 46 2.4 THE ACOUSTIC ENVIRONMENT 47 2.4.1 AMBIENT NOISE 47 2.4.2
ECHO AND REVERBERATION 48 2.4.3 SIGNAL-TO-NOISE AND
SIGNAL-TO-REVERBERATION RATIO 51 2.4.4 AN ILLUSTRATIVE COMPARISON
BETWEEN CLOSE AND DISTANT RECORDINGS 52 2.4.5 THE INFLUENCE OF THE
ACOUSTIC ENVIRONMENT ON SPEECH PRODUCTION 53 2.4.6 COLORATION 54 2.4.7
HEAD ORIENTATION AND SOUND RADIATION 55 2.4.8 EXPECTED DISTANCES BETWEEN
THE SPEAKER AND THE MICROPHONE 57 2.5 RECORDING TECHNIQUES AND SENSOR
CONFIGURATION 58 2.5.7 MECHANICAL CLASSIFICATION OF MICROPHONES 58
2.5.2 ELECTRICAL CLASSIFICATION OF MICROPHONES 59 2.5.3 CHARACTERISTICS
OF MICROPHONES 60 2.5.4 MICROPHONE PLACEMENT 60 2.5.5 MICROPHONE
AMPLIFICATION 62 2.6 SUMMARY AND FURTHER READING 62 2.7 PRINCIPAL
SYMBOLS 63 3 SIGNAL PROCESSING AND FILTERING TECHNIQUES 65 3.1 LINEAR
TIME-INVARIANT SYSTEMS 65 3.7.7 TIME DOMAIN ANALYSIS 66 3.7.2 FREQUENCY
DOMAIN ANALYSIS 69 3.7.3 Z-TRANSFORM ANALYSIS 72 3.7.4 SAMPLING
CONTINUOUS-TIME SIGNALS 79 3.2 THE DISCRETE FOURIER TRANSFORM 82 3.2.7
REALIZING LTI SYSTEMS WITH THE DFT 85 3.2.2 OVERLAP-ADD METHOD 86 3.2.3
OVERLAP-SAVE METHOD 87 3.3 SHORT-TIME FOURIER TRANSFORM 87 3.4 SUMMARY
AND FURTHER READING 90 3.5 PRINCIPAL SYMBOLS 91 CONTENTS VII 4 BAYESIAN
FILTERS 93 4.1 SEQUENTIAL BAYESIAN ESTIMATION 95 4.2 WIENER FILTER 98
4.2.1 TIME DOMAIN SOLUTION 98 4.2.2 FREQUENCY DOMAIN SOLUTION 99 4.3
KALMAN FILTER AND VARIATIONS 101 4.3.1 KALMAN FILTER 101 4.3.2 EXTENDED
KALMAN FILTER 106 4.3.3 ITERATED EXTENDED KALMAN FILTER 107 4.3.4
NUMERICAL STABILITY 108 4.3.5 PROBABILISTIC DATA ASSOCIATION FILTER 110
4.3.6 JOINT PROBABILISTIC DATA ASSOCIATION FILTER 115 4.4 PARTICLE
FILTERS 121 4.4.1 APPROXIMATION OF PROBABILISTIC EXPECTATIONS 121 4.4.2
SEQUENTIAL MONTE CARLO METHODS 125 4.5 SUMMARY AND FURTHER READING 132
4.6 PRINCIPAL SYMBOLS 133 5 SPEECH FEATURE EXTRACTION 135 5.1 SHORT-TIME
SPECTRAL ANALYSIS 136 5.7.7 SPEECH WINDOWING AND SEGMENTATION 136 5.7.2
THE SPECTROGRAM 137 5.2 PERCEPTUALLY MOTIVATED REPRESENTATION . 138
5.2.7 SPECTRAL SHAPING 138 5.2.2 BARK AND MEL FILTER BANKS 139 5.2.3
WARPING BY BILINEAR TRANSFORM - TIME VS FREQUENCY DOMAIN 142 5.3
SPECTRAL ESTIMATION AND ANALYSIS 145 5.3.7 POWER SPECTRUM 145 5.3.2
SPECTRAL ENVELOPES 146 5.3.3 LP ENVELOPE 147 5.3.4 MVDR ENVELOPE 150
5.3.5 PERCEPTUAL LP ENVELOPE 153 5.3.6 WARPED LP ENVELOPE 153 5.3.7
WARPED MVDR ENVELOPE 156 5.3.8 WARPED-TWICE MVDR ENVELOPE 157 5.3.9
COMPARISON OF SPECTRAL ESTIMATES 159 5.3.70 SCALING OF ENVELOPES 160 5.4
CEPSTRAL PROCESSING 163 5.4.7 DEFINITION AND CHARACTERISTICS OF CEPSTRAL
SEQUENCES 163 5.4.2 HOMOMORPHIC DECONVOLUTION 166 5.4.3 CALCULATING
CEPSTRAL COEFFICIENTS 16 7 5.5 COMPARISON BETWEEN MEL FREQUENCY,
PERCEPTUAL LP AND WARPED MVDR CEPSTRAL COEFFICIENT FRONT-ENDS 168 5.6
FEATURE AUGMENTATION 169 5.6.7 STATIC AND DYNAMIC PARAMETER AUGMENTATION
169 VIII CONTENTS 5.6.2 FEATURE AUGMENTATION BY TEMPORAL PATTERNS 171
5.7 FEATURE REDUCTION 171 5.7.7 CLASS SEPARABILITY MEASURES 172 5.7.2
LINEAR DISCRIMINANT ANALYSIS 173 5.7.3 HETEROSCEDASTIC LINEAR
DISCRIMINANT ANALYSIS 176 5.8 FEATURE-SPACE MINIMUM PHONE ERROR 178 5.9
SUMMARY AND FURTHER READING 178 5.10 PRINCIPAL SYMBOLS 179 6 SPEECH
FEATURE ENHANCEMENT 181 6.1 NOISE AND REVERBERATION IN VARIOUS DOMAINS
183 6.7.7 FREQUENCY DOMAIN 183 6.7.2 POWER SPECTRAL DOMAIN 185 6.7.3
LOGARITHMIC SPECTRAL DOMAIN 186 6.1.4 CEPSTRAL DOMAIN 187 6.2 TWO
PRINCIPAL APPROACHES 188 6.3 DIRECT SPEECH FEATURE ENHANCEMENT 189 6.3.7
WIENER FILTER 189 6.3.2 GAUSSIAN AND SUPER-GAUSSIAN MMSE ESTIMATION 191
6.3.3 RASTA PROCESSING 191 6.3.4 STEREO-BASED PIECEWISE LINEAR
COMPENSATION FOR ENVIRONMENTS 192 6.4 SCHEMATICS OF INDIRECT SPEECH
FEATURE ENHANCEMENT 193 6.5 ESTIMATING ADDITIVE DISTORTION 194 6.5.7
VOICE ACTIVITY DETECTION-BASED NOISE ESTIMATION 194 6.5.2 MINIMUM
STATISTICS NOISE ESTIMATION 195 6.5.3 HISTOGRAM-AND QUANTILE-BASED
METHODS 196 6.5.4 ESTIMATION OF THE A POSTERIORI AND A PRIORI
SIGNAL-TO-NOISE RATIO 197 6.6 ESTIMATING CONVOLUTIONAL DISTORTION 198
6.6.7 ESTIMATING CHANNEL EFFECTS 199 6.6.2 MEASURING THE IMPULSE
RESPONSE 200 6.6.3 HARMFUL EFFECTS OF ROOM ACOUSTICS 201 6.6.4 PROBLEM
IN SPEECH DEREVERBERATION 201 6.6.5 ESTIMATING LATE REFLECTIONS 202 6.7
DISTORTION EVOLUTION 204 6.7.7 RANDOM WALK 204 6.7.2 SEMI-RANDOM WALK BY
POLYAK AVERAGING AND FEEDBACK 205 6.7.3 PREDICTED WALK BY STATIC
AUTOREGRESSIVE PROCESSES 206 6.7.4 PREDICTED WALK BY DYNAMIC
AUTOREGRESSIVE PROCESSES 207 6. 7.5 PREDICTED WALK BY EXTENDED KALMAN
FILTERS 209 6.7.6 CORRELATED PREDICTION ERROR COVARIANCE MATRIX 210 6.8
DISTORTION EVALUATION 211 6.5.7 LIKELIHOOD EVALUATION 212 6.8.2
LIKELIHOOD EVALUATION BY A SWITCHING MODEL 213 6.8.3 INCORPORATING THE
PHASE 214 6.9 DISTORTION COMPENSATION 215 CONTENTS IX 6.9.7 SPECTRAL
SUBTRACTION 215 6.9.2 COMPENSATING FOR CHANNEL EFFECTS 217 6.9.3
DISTORTION COMPENSATION FOR DISTRIBUTIONS 218 6.10 JOINT ESTIMATION OF
ADDITIVE AND CONVOLUTIONAL DISTORTIONS 222 6.11 OBSERVATION UNCERTAINTY
227 6.12 SUMMARY AND FURTHER READING 228 6.13 PRINCIPAL SYMBOLS 229 7
SEARCH: FINDING THE BEST WORD HYPOTHESIS 231 7.1 FUNDAMENTALS OF SEARCH
233 7.7.7 HIDDEN MARKOV MODEL: DEFINITION 233 7.7.2 VITERBI ALGORITHM
235 7.7.3 WORD LATTICE GENERATION 238 7.1.4 WORD TRACE DECODING 240 7.2
WEIGHTED FINITE-STATE TRANSDUCERS 241 7.2.7 DEFINITIONS 241 7.2.2
WEIGHTED COMPOSITION 244 7.2.3 WEIGHTED DETERMINIZATION 246 7.2.4 WEIGHT
PUSHING 249 7.2.5 WEIGHTED MINIMIZATION 25 1 7.2.6 EPSILON REMOVAL 253
7.3 KNOWLEDGE SOURCES 255 7.3.7 GRAMMAR , 256 7.3.2 PRONUNCIATION
LEXICON 263 7.3.3 HIDDEN MARKOV MODEL 264 7.3.4 CONTEXT DEPENDENCY
DECISION TREE 264 7.3.5 COMBINATION OF KNOWLEDGE SOURCES 273 7.3.6
REDUCING SEARCH GRAPH SIZE 274 7.4 FAST ON-THE-FLY COMPOSITION 275 7.5
WORD AND LATTICE COMBINATION 278 7.6 SUMMARY AND FURTHER READING 279 7.7
PRINCIPAL SYMBOLS 281 8 HIDDEN MARKOV MODEL PARAMETER ESTIMATION 283 8.1
MAXIMUM LIKELIHOOD PARAMETER ESTIMATION 284 8.7.7 GAUSSIAN MIXTURE MODEL
PARAMETER ESTIMATION 286 8.1.2 FORWARD-BACKWARD ESTIMATION 290 8.7.3
SPEAKER-ADAPTED TRAINING 296 8.1.4 OPTIMAL REGRESSION CLASS ESTIMATION
300 8.7.5 VITERBI AND LABEL TRAINING 301 8.2 DISCRIMINATIVE PARAMETER
ESTIMATION 302 8.2.7 CONVENTIONAL MAXIMUM MUTUAL INFORMATION ESTIMATION
FORMULAE 302 8.2.2 MAXIMUM MUTUAL INFORMATION TRAINING ON WORD LATTICES
306 8.2.3 MINIMUM WORD AND PHONE ERROR TRAINING 30 8 CONTENTS 8.2.4
MAXIMUM MUTUAL INFORMATION SPEAKER-ADAPTED TRAINING 310 8.3 SUMMARY AND
FURTHER READING 313 8.4 PRINCIPAL SYMBOLS 315 9 FEATURE AND MODEL
TRANSFORMATION 317 9.1 FEATURE TRANSFORMATION TECHNIQUES 318 9.7.7 VOCAL
TRACT LENGTH NORMALIZATION 318 9.7.2 CONSTRAINED MAXIMUM LIKELIHOOD
LINEAR REGRESSION 319 9.2 MODEL TRANSFORMATION TECHNIQUES 320 9.2.7
MAXIMUM LIKELIHOOD LINEAR REGRESSION 321 9.2.2 ALL-PASS TRANSFORM
ADAPTATION 322 9.3 ACOUSTIC MODEL COMBINATION 332 9.3.7 COMBINATION OF
GAUSSIANS IN THE LOGARITHMIC DOMAIN 333 9.4 SUMMARY AND FURTHER READING
334 9.5 PRINCIPAL SYMBOLS 336 10 SPEAKER LOCALIZATION AND TRACKING 337
10.1 CONVENTIONAL TECHNIQUES 338 10.1.1 SPHERICAL INTERSECTION ESTIMATOR
339 10.1.2 SPHERICAL INTERPOLATION ESTIMATOR 341 10.1.3 LINEAR
INTERSECTION ESTIMATOR 342 10.2 SPEAKER TRACKING WITH THE KALMAN FILTER
, 345 10.2.1 IMPLEMENTATION BASED ON THE CHOLESKY DECOMPOSITION 348 10.3
TRACKING MULTIPLE SIMULTANEOUS SPEAKERS 351 10.4 AUDIO-VISUAL SPEAKER
TRACKING 352 10.5 SPEAKER TRACKING WITH THE PARTICLE FILTER 354 10.5.1
LOCALIZATION BASED ON TIME DELAYS OF ARRIVAL 356 10.5.2 LOCALIZATION
BASED ON STEERED BEAMFORMER RESPONSE POWER 356 10.6 SUMMARY AND FURTHER
READING 357 10.7 PRINCIPAL SYMBOLS 358 11 DIGITAL FILTER BANKS 359 11.1
UNIFORM DISCRETE FOURIER TRANSFORM FILTER BANKS 360 11.2 POLYPHASE
IMPLEMENTATION 364 11.3 DECIMATION AND EXPANSION 365 11.4 NOBLE
IDENTITIES 368 11.5 NYQUIST(M) FILTERS 369 11.6 FILTER BANK DESIGN OF DE
HAAN ET AL. 371 11.6.1 ANALYSIS PROTOTYPE DESIGN 372 77.6.2 SYNTHESIS
PROTOTYPE DESIGN 375 11.7 FILTER BANK DESIGN WITH THE NYQUIST(M)
CRITERION 376 77.7.7 ANALYSIS PROTOTYPE DESIGN 376 11.7.2 SYNTHESIS
PROTOTYPE DESIGN 311 11.7.3 ALTERNATIVE DESIGN 378 CONTENTS XI 11.8
QUALITY ASSESSMENT OF FILTER BANK PROTOTYPES 379 11.9 SUMMARY AND
FURTHER READING 384 11.10 PRINCIPAL SYMBOLS 384 12 BLIND SOURCE
SEPARATION 387 12.1 CHANNEL QUALITY AND SELECTION 388 12.2 INDEPENDENT
COMPONENT ANALYSIS 390 72.2.7 DEFINITION OF ICA 390 12.2.2 STATISTICAL
INDEPENDENCE AND ITS IMPLICATIONS 39 2 72.2.3 ICA OPTIMIZATION CRITERIA
396 12.2.4 PARAMETER UPDATE STRATEGIES 403 12.3 BSS ALGORITHMS BASED ON
SECOND-ORDER STATISTICS 404 12.4 SUMMARY AND FURTHER READING 407 12.5
PRINCIPAL SYMBOLS 408 13 BEAMFORMING 409 13.1 BEAMFORMING FUNDAMENTALS
411 13.1.1 SOUND PROPAGATION AND ARRAY GEOMETRY 411 73.7.2 BEAM PATTERNS
415 73.7.3 DELAY-AND-SUM BEAMFORMER 416 73.7.4 BEAM STEERING 421 13.2
BEAMFORMING PERFORMANCE MEASURES 426 73.2.7 DIRECTIVITY . 426 73.2.2
ARRAY GAIN 428 13.3 CONVENTIONAL BEAMFORMING ALGORITHMS 430 13.3.1
MINIMUM VARIANCE DISTORTIONLESS RESPONSE BEAMFORMER 430 73.3.2 ARRAY
GAIN OF THE MVDR BEAMFORMER 433 13.3.3 MVDR BEAMFORMER PERFORMANCE WITH
PLANE WAVE INTERFERENCE 433 13.3.4 SUPERDIRECTIVE BEAMFORMERS 437 73.3.5
MINIMUM MEAN SQUARE ERROR BEAMFORMER 439 13.3.6 MAXIMUM SIGNAL-TO-NOISE
RATIO BEAMFORMER 441 13.3.7 GENERALIZED SIDELOBE CANCELER 441 13.3.8
DIAGONAL LOADING 445 13.4 RECURSIVE ALGORITHMS 447 73.4.7 GRADIENT
DESCENT ALGORITHMS 448 73.4.2 LEAST MEAN SQUARE ERROR ESTIMATION 450
13.4.3 RECURSIVE LEAST SQUARES ESTIMATION 455 13.4.4 SQUARE-ROOT
IMPLEMENTATION OF THE RLS BEAMFORMER 461 13.5 NONCONVENTIONAL
BEAMFORMING ALGORITHMS 465 13.5.1 MAXIMUM LIKELIHOOD BEAMFORMING 466
13.5.2 MAXIMUM NEGENTROPY BEAMFORMING ALL 13.5.3 HIDDEN MARKOV MODEL
MAXIMUM NEGENTROPY BEAMFORMING ALL 13.5.4 MINIMUM MUTUAL INFORMATION
BEAMFORMING 480 73.5.5 GEOMETRIC SOURCE SEPARATION 487 XII CONTENTS 13.6
ARRAY SHAPE CALIBRATION 488 13.7 SUMMARY AND FURTHER READING 489 13.8
PRINCIPAL SYMBOLS 491 14 HANDS ON 493 14.1 EXAMPLE ROOM CONFIGURATIONS
494 14.2 AUTOMATIC SPEECH RECOGNITION ENGINES 496 14.3 WORD ERROR RATE
498 14.4 SINGLE-CHANNEL FEATURE ENHANCEMENT EXPERIMENTS 499 14.5
ACOUSTIC SPEAKER-TRACKING EXPERIMENTS 501 14.6 AUDIO-VIDEO
SPEAKER-TRACKING EXPERIMENTS 503 14.7 SPEAKER-TRACKING PERFORMANCE VS
WORD ERROR RATE 504 14.8 SINGLE-SPEAKER BEAMFORMING EXPERIMENTS 505 14.9
SPEECH SEPARATION EXPERIMENTS 507 14.10 FILTER BANK EXPERIMENTS 508
14.11 SUMMARY AND FURTHER READING 509 APPENDICES 511 A LIST OF
ABBREVIATIONS 513 B USEFUL BACKGROUND 517 B.I DISCRETE COSINE TRANSFORM
* 517 B.2 MATRIX INVERSION LEMMA 518 B.3 CHOLESKY DECOMPOSITION 519 B.4
DISTANCE MEASURES 519 B.5 SUPER-GAUSSIAN PROBABILITY DENSITY FUNCTIONS
521 B.5.7 GENERALIZED GAUSSIAN PDF 521 B.5.2 SUPER-GAUSSIAN PDFS WITH
THE MEIER G-FUNCTION 523 B.6 ENTROPY 528 B.7 RELATIVE ENTROPY 529 B.8
TRANSFORMATION LAW OF PROBABILITIES 529 B.9 CASCADE OF WARPING STAGES
530 B.10 TAYLOR SERIES 530 B.LL CORRELATION AND COVARIANCE 531 B.12
BESSEL FUNCTIONS 531 B.13 PROOF OF THE NYQUIST-SHANNON SAMPLING THEOREM
532 B.14 PROOF OF EQUATIONS (11.31-11.32) 532 B.I5 GIVENS ROTATIONS 534
B.16 DERIVATIVES WITH RESPECT TO COMPLEX VECTORS 537 B.17 PERPENDICULAR
PROJECTION OPERATORS 540 BIBLIOGRAPHY 541 INDEX 561
|
| any_adam_object | 1 |
| author | Wölfel, Matthias |
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| dewey-full | 006.4/54 |
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| dewey-search | 006.4/54 |
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| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik Sprachwissenschaft Literaturwissenschaft |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV035604564 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T21:41:27Z |
| institution | BVB |
| isbn | 9780470517048 |
| language | English |
| lccn | 2008052791 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-017659817 |
| oclc_num | 262719141 |
| open_access_boolean | |
| owner | DE-634 DE-29T DE-11 DE-355 DE-BY-UBR |
| owner_facet | DE-634 DE-29T DE-11 DE-355 DE-BY-UBR |
| physical | XIX, 573 S. graph. Darst. |
| publishDate | 2009 |
| publishDateSearch | 2009 |
| publishDateSort | 2009 |
| publisher | Wiley |
| record_format | marc |
| spelling | Wölfel, Matthias Verfasser (DE-588)138060061 aut Distant speech recognition Matthias Wölfel and John McDonough 1. publ. Chichester Wiley 2009 XIX, 573 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Automatic speech recognition Automatische Spracherkennung (DE-588)4003961-4 gnd rswk-swf Automatische Spracherkennung (DE-588)4003961-4 s DE-604 McDonough, John Sonstige oth HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017659817&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Wölfel, Matthias Distant speech recognition Automatic speech recognition Automatische Spracherkennung (DE-588)4003961-4 gnd |
| subject_GND | (DE-588)4003961-4 |
| title | Distant speech recognition |
| title_auth | Distant speech recognition |
| title_exact_search | Distant speech recognition |
| title_full | Distant speech recognition Matthias Wölfel and John McDonough |
| title_fullStr | Distant speech recognition Matthias Wölfel and John McDonough |
| title_full_unstemmed | Distant speech recognition Matthias Wölfel and John McDonough |
| title_short | Distant speech recognition |
| title_sort | distant speech recognition |
| topic | Automatic speech recognition Automatische Spracherkennung (DE-588)4003961-4 gnd |
| topic_facet | Automatic speech recognition Automatische Spracherkennung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017659817&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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