Rao / Sarkar Robust Speaker Recognition in Noisy Environments

1. Auflage 2014
ISBN: 978-3-319-07130-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 139 Seiten, eBook

Reihe: SpringerBriefs in Speech Technology

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.

Zielgruppe

Research

Autoren/Hrsg.

Rao, K. Sreenivasa

Sarkar, Sourjya

Inhaltsverzeichnis

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.

Über Autor(innen)

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.