基于声学矢量传感器阵列和稀疏表示的语音声源方位角估计方法研究

项目名称： 基于声学矢量传感器阵列和稀疏表示的语音声源方位角估计方法研究

项目编号： No.61271309

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 无线电电子学、电信技术

项目作者： 邹月娴

作者单位： 北京大学

项目金额： 72万元

中文摘要： 空间语音声源方位角（DOA）估计是服务机器人听觉系统的关键技术之一，具有重要的应用价值。由于服务机器人听觉系统面临自身设备噪声、时变环境噪声和多声源并存等不利因素，采用传统的声源DOA估计技术在估计精度和稳定性方面都不能满足其应用需求。本项目拟在稀疏表示理论框架下，创新开展基于声学矢量传感器（AVS）阵列的高精度、鲁棒、多语音声源DOA估计新理论和新方法研究。拟深入研究语音声源空域稀疏性、语音时频稀疏特性、语音信号的稀疏表示方法、AVS阵列耦合特性及子阵列声源信息关联性，重点研究基于AVS阵列的宽带导向矢量模型、声源过完备词典和DOA稀疏表示模型的有效构建方法。研究与之对应的稀疏矢量重构准则，采用凸优化理论推导最优求解快速算法，并注重研究正则参数的优化选取原则以提高算法在噪声中的鲁棒性。通过实际环境下的语音声源DOA估计实验来验证本项目所提出的语音声源DOA估计方法的可行性与有效性。

中文关键词： 到达方位角估计；稀疏表示；声学矢量传感器阵列；凸优化；服务机器人语音声源

英文摘要： Estimation of the direction-of-arrival (DOA) of the spatial speech sources is one of the key techniques in the audition system of the service robot, which is of significant application value. Since there are several adverse factors in the audition system of the service robot, such as the device noise, time-varying environment noise and multiple spatial speech sources, the traditional DOA estimation techniques failed to meet its requirements in terms of the estimation accuracy and the robustness to the noise. This project aims at studying and developing the new methodology and techniques of the high resolution and robust speech source DOA estimation based on the acoustic vector sensor (AVS) array under the sparse representation framework. The spatial sparsity of the speech source, the time-frequency sparsity of the speech signal, the sparse representation of the speech signal, AVS array coupling properties and its source information correlation will be fully investigated. The focus will be on the methods of modeling the AVS array steering vector for wideband sources, the overcomplete basis of the source, and the DOA sparse representation. The corresponding study of the reconstruction criterion of the sparse vector will be carried out, and the derivation of the fast algorithm for the optimal solution of the sparse

英文关键词： Direction of Arrival；Sparse Representation；Acoustic Vector Sensor Array；Convex Optimization；Service Robot Speech Source