Robust Speaker Recognition in Noisy Environments
Seiten
2014
|
2014
Springer International Publishing (Verlag)
978-3-319-07129-9 (ISBN)
Springer International Publishing (Verlag)
978-3-319-07129-9 (ISBN)
This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.
K. Sreenivasa Rao, Associate Professor, School of Information Technology, Indian Institute of Technology Kharagpur (IIT Kharagpur). Sourjya Sarkar is a graduate student at the Indian Institute of Technology Kharagpur.
Robust Speaker Verification - A Review.- Speaker Verification in Noisy Environments using Gaussian Mixture Models.- Stochastic Feature Compensation for Robust Speaker Verification.- Robust Speaker Modeling for Speaker Verification in Noisy Environments.
Erscheint lt. Verlag | 17.7.2014 |
---|---|
Reihe/Serie | SpringerBriefs in Speech Technology |
Zusatzinfo | XII, 139 p. 31 illus., 25 illus. in color. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 234 g |
Themenwelt | Mathematik / Informatik ► Informatik |
Technik ► Elektrotechnik / Energietechnik | |
Schlagworte | Feature Compensation using Multiple Background Mod • Feature Compensation using Multiple Background Models • Robust Speaker Recognition in Noisy Environment • Robust Speaker Recognition using I-vectors • Robust Speaker Verification using GMM-SVM Framewor • Robust Speaker Verification using GMM-SVM Framework • Speaker Recognition in Noisy Background • Speaker Recognition in Varying Background • Speaker Verification in Noisy Background • Speaker Verification using Super-vectors • Stochastic Feature Compensation for Robust Speaker • Stochastic Feature Compensation for Robust Speaker Recognition • Total Variability Modeling for Robust Speaker Reco • Total Variability Modeling for Robust Speaker Recognition |
ISBN-10 | 3-319-07129-7 / 3319071297 |
ISBN-13 | 978-3-319-07129-9 / 9783319071299 |
Zustand | Neuware |
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