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ICASSP
2011
IEEE

NAP for high level language identification

8 years 3 months ago
NAP for high level language identification
Varying channel conditions present a difficult problem for many speech technologies such as language identification (LID). Channel compensation techniques have been shown to significantly improve performance in LID for acoustic systems [1]. For high-level token systems, nuisance attribute projection (NAP) has been shown to perform well in the context of speaker identification [2]. In this work, we describe a novel approach to dealing with the high dimensional sparse NAP training problem as applied to a 4-gram phonotactic LID system [3] run on the NIST 2009 Language Recognition Evaluation (LRE) [4] task. We demonstrate performance gains on the Voice of America (VOA) portion of the 2009 LRE data.
Fred S. Richardson, William M. Campbell
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Fred S. Richardson, William M. Campbell
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