.png){kind=icon}
返回
Multimodal speaker identification using an adaptive classifier cascade based on modality reliability
.png){kind=icon}
OA
AI
DOI：10.1109/TMM.2005.854464.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present a multimodal open-set speaker identification system that integrates information coming from audio, face and lip motion modalities. For fusion of multiple modalities, we propose a new adaptive cascade rule that favors reliable modality combinations through a cascade of classifiers. The order of the classifiers in the cascade is adaptively determined based on the reliability of each modality combination. A novel reliability measure, that genuinely fits to the open-set speaker identification problem, is also proposed to assess accept or reject decisions of a classifier. A formal framework is developed based on probability of correct decision for analytical comparison of the proposed adaptive rule with other classifier combination rules. The proposed adaptive rule is more robust in the presence of unreliable modalities, and outperforms the hard-level max rule and soft-level weighted summation rule, provided that the employed reliability measure is effective in assessment of classifier decisions. Experimental results that support this assertion are provided.
Keyword:
classifier combining
modality reliability
multimodal speaker identification
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.7
论文数:
4.5K
被引数:
2.4W
机构
暂无机构信息
引用论文
分享收藏分享收藏
分享收藏The nuclear factor erythroid 2-like 2 activator, tert-butylhydroquinone, improves cognitive performance in mice after mild traumatic brain injury.png)
NeuroscienceOAAI
NeuroscienceIF0
OAAI分享收藏Photoinduced Electron and Energy Transfer in a Molecular Triad Featuring a Fullerene Redox MediatorOAAI
OAAI分享收藏分享收藏
查看更多内容