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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xi Zhou Navrdtit, J. Pelecanos, J.W. Ramaswamy, G.N. Huang, T.S. |
| Copyright Year | 2008 |
| Description | Author affiliation: Dept. of ECE, Univ. of Illinois at Urbana-Champaign, Urbana, IL (Xi Zhou) |
| Abstract | Gaussian mixture models (QMM) have become one of the standard acoustic approaches for Language Detection. These models are typically incorporated to produce a log-likelihood ratio (LLR) verification statistic. In this framework, the intersession variability within each language becomes an adverse factor degrading the accuracy. To address this problem, we formulate the LLR as a function of the QMM parameters concatenated into normalized mean supervectors, and estimate the distribution of each language in this (high dimensional) supervector space. The goal is to de-emphasize the directions with the largest intersession variability. We compare this method with two other popular intersession variability compensation methods known as Nuisance Attribute Projection (NAP) and Within-Class Covariance Normalization (WCCN). Experiments on the NIST LRE 2003 and NIST LRE 2005 speech corpora show that the presented technique reduces the error by 50% relative to the baseline, and performs competitively with the NAP and WCCN approaches. Fusion results with a phonotactic component are also presented. |
| Starting Page | 4157 |
| Ending Page | 4160 |
| File Size | 282981 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424414833 |
| ISSN | 15206149 |
| DOI | 10.1109/ICASSP.2008.4518570 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-03-31 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines NIST Concatenated codes Kernel Acoustic signal detection Speech Testing Databases Speaker recognition Support vector machine classification ISV WCCN-LLR NAP |
| Content Type | Text |
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