.png){kind=icon}
返回
Distributed Expectation-Maximization Algorithm for Speaker Localization in Reverberant Environments
.png){kind=icon}
PRE
AI
DOI：10.1109/TASLP.2017.2788198.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Localization of acoustic sources has attracted a considerable amount of research attention in recent years. A major obstacle to achieving high localization accuracy is the presence of reverberation, the influence of which obviously increases with the number of active speakers in the room. Human hearing is capable of localizing acoustic sources even in extreme conditions. In this study, we propose to combine a method based on human hearing mechanisms and a modified incremental distributed expectation-maximization (IDEM) algorithm. Rather than using phase difference measurements that are modeled by a mixture of complex-valued Gaussians, as proposed in the original IDEM framework, we propose to use time difference of arrival measurements in multiple subbands and model them by a mixture of real-valued truncated Gaussians. Moreover, we propose to first filter the measurements in order to reduce the effect of the multipath conditions. The proposed method is evaluated using both simulated data and real-life recordings.
Keyword:
Precedence effect
onset dominance
distributed expectation-maximization
auditory scene analysis
sound source localization
spectral masking
incremental expectation-maximization
truncated Gaussian
multi-path
time difference of arrival
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
I
IF:
5.1
论文数:
2.6K
被引数:
1.1W
机构
引用论文
Sediment and Turbidity Associated with Offshore Dredging Increase Coral Disease Prevalence on Nearby Reefs.png)
PLoS ONE
OAAI
PLoS ONEIF0
OAAI分享收藏Dry Fractionation of Plant-Based Proteins for Better Meat Analogue Applications植物基蛋白的干法分离以改善肉类模拟应用
OAAI
OAAI分享收藏
查看更多内容