| 书目名称 | Robust Speaker Recognition in Noisy Environments |
| 编辑 | K. Sreenivasa Rao,Sourjya Sarkar |
| 视频video | |
| 概述 | Discusses the effect of noise, stochastic feature compensation methods based on Gaussian Mixture models (GMMs).Demonstrates the standards for speaker databases and noisy environments.Includes suppleme |
| 丛书名称 | SpringerBriefs in Speech Technology |
| 图书封面 |  |
| 描述 | 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. |
| 出版日期 | Book 2014 |
| 关键词 | Feature Compensation using Multiple Background Models; Robust Speaker Recognition in Noisy Environmen |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-07130-5 |
| isbn_softcover | 978-3-319-07129-9 |
| isbn_ebook | 978-3-319-07130-5Series ISSN 2191-737X Series E-ISSN 2191-7388 |
| issn_series | 2191-737X |
| copyright | The Author(s) 2014 |
发表于 2025-3-21 17:36:48
