面向船载远程会议的麦克风阵列高精度DOA估计  

High precision DOA estimation of microphone array for shipboard teleconferencing

作　　者：刘雨佶 童峰[1,2,3] 陈东升 卢荣富[4] 冯万健 Liu Yuji;Tong Feng;Chen Dongsheng;Lu Rongfu;Feng Wanjian(Key Laboratory of Underwater Acoustic Communication and Marine Information Technique of the Ministry of Education,Xiamen University,Xiamen 361002,China;College of Earth and Ocean Sciences,Xiamen University,Xiamen 361002,China;Shenzhen Research Institute of Xiamen University,Shenzhen 518000,China;Xiamen Yilian Network Technology Co.,Ltd.,Xiamen 361000,China)

机构地区：[1]厦门大学水声通信与海洋信息技术教育部重点实验室,福建厦门361002 [2]厦门大学海洋与地球学院,福建厦门361002 [3]厦门大学深圳研究院,广东深圳518000 [4]厦门亿联网络技术股份有限公司,福建厦门361000

出　　处：《电子技术应用》2022年第3期32-36,77,共6页Application of Electronic Technique

基　　金：国家自然科学基金(11274259);深圳虚拟大学园扶持经费研发机构建设项目(YFJGJS1.0)。

摘　　要：随着船舶智能化水平提高,船载远程会议系统对提高应急处理能力、推进船岸一体化网络建设有重要意义,麦克风阵列是保证远程会议系统语音效果和支持多模态交互的重要语音前端。但船舶舱室狭小尺寸一方面导致只能采用小尺寸麦阵,另一方面小舱室导致的强混响以及嘈杂舱室噪声也使传统麦克风阵列算法性能严重下降。考虑船舶舱室复杂环境下小尺寸麦阵DOA估计场景,提出了一种轻量级Mask-DOA估计神经网络模型。该方法在DOA估计神经网络引入Mask算法降低噪声和混响的干扰,并提取增强后的GCC-PHAT作为网络特征,从而在小尺寸麦阵上实现高精度DOA估计。仿真和实验结果表明,所提出的Mask-DOA模型面对复杂的船舶舱室环境更鲁棒,泛化能力更强。With the improvement of ship intelligence level,shipboard teleconferencing system is of great significance to improve the emergency handling capacity and promote the construction of shipboard integrated network.Microphone array is an important voice front-end to ensure the voice effect as well as the multi-mode interaction of teleconferencing system.However,while the small size of ship cabins leads to the adoption of small-size array,strong reverberation caused by small cabins and noisy cabin noise also seriously degrade the performance of traditional microphone array algorithm.Considering the direction of arrival(DOA)estimation scenario of small-size array in complex environment of ship cabin,a lightweight Mask-DOA estimation neural network model is proposed in this paper.With this method,Mask algorithm is introduced into the DOA estimation neural network to reduce the noise and reverb interference,then the enhanced GCC-PHAT is extracted as the network feature,so as to realize the high-precision DOA estimation on the small-size microphone array.Simulation and experimental results show that the Mask-DOA model proposed in this paper is more robust and has better generalization ability in the complex environment of ship cabin.

关 键 词：波达方向估计 船舶舱室噪声混响环境 神经网络 时频掩蔽 

分 类 号：TN912.3[电子电信—通信与信息系统]