利用退化解混估计技术和带轨道管理的基数平衡多目标多伯努利滤波器(DUET-CBMeMBer)对多声源进行跟踪和识别

Nicholas Chong, Shanhung Wong, S. Nordholm, I. Murray
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引用次数: 5

摘要

在源分离研究中,“鸡尾酒会问题”是源分离研究要解决的一个具有挑战性的问题。为了解决这个复杂的问题,人们作了许多尝试。一个合乎逻辑的方法是把这个复杂的问题分解成几个较小的问题,在不同的阶段解决——每个阶段考虑不同的方面。在本文中,我们通过定位和跟踪房间环境中的多个移动语音源,为部分问题提供了一个鲁棒的解决方案。本文研究了未知数量运动源的分离问题。我们概述的DUET-CBMeMBer方法能够估计声源的数量以及跟踪和标记它们。本文提出了一种基于声源轨迹识别声源的轨道管理技术,作为DUET-CBMeMBer技术的扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multiple sound source tracking and identification via degenerate unmixing estimation technique and cardinality balanced multi-target multi-bernoulli filter (DUET-CBMeMBer) with track management
In Source Separation research, "cocktail party problem" is a challenging problem that research into source separation aims to solve. Many attempts have been made to solve this complex problem. A logical approach would be to break down this complex problem into several smaller problems which are solved in different stages - each considering various aspects. In this paper, we are providing a robust solution to a part of the problem by localizing and tracking multiple moving speech sources in a room environment. Here we study the separation problem for unknown number of moving sources. The DUET-CBMeMBer method we outline is capable of estimating the number of sound sources as well as tracking and labelling them. This paper proposes a track management technique that identifies sound sources based on their trajectory as an extension to the DUET-CBMeMBer technique.
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