中圖分類號： TN912.3 文獻標識碼： A DOI：10.16157/j.issn.0258-7998.212108 中文引用格式： 劉雨佶,，童峰，陳東升,，等. 面向船載遠程會議的麥克風陣列高精度DOA估計[J].電子技術(shù)應用,，2022，48(3)：32-36,，77. 英文引用格式： Liu Yuji,，Tong Feng，Chen Dongsheng,，et al. High precision DOA estimation of microphone array for shipboard teleconferencing[J]. Application of Electronic Technique,，2022，48(3)：32-36,，77.
High precision DOA estimation of microphone array for shipboard teleconferencing
Liu Yuji1,，2，3,，Tong Feng1,，2，3,，Chen Dongsheng1,，2，3,，Lu Rongfu4,，F(xiàn)eng Wanjian4
1.Key Laboratory of Underwater Acoustic Communication and Marine Information Technique of the Ministry of Education， Xiamen University,，Xiamen 361002,，China； 2.College of Earth and Ocean Sciences,，Xiamen University,，Xiamen 361002，China,； 3.Shenzhen Research Institute of Xiamen University,，Shenzhen 518000，China,； 4.Xiamen Yilian Network Technology Co.,，Ltd.，Xiamen 361000,，China
Abstract： 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.
Key words : direction of arrival estimation,；ship cabin noise and reverberation environment；neural network,；time-frequency masking
0 引言
船載遠程會議系統(tǒng)在船舶智能化方面發(fā)揮著顯著作用,，特別是可提高應急處理能力,，推進船岸一體化網(wǎng)絡建設(shè)。近些年來,，船載遠程會議監(jiān)測系統(tǒng)發(fā)展迅速[1-3],。麥克風陣列通過提供準確波達方向(Direction Of Arrival，DOA)估計可實現(xiàn)語音增強處理,同時還可以為遠程會議系統(tǒng)攝像機提供說話人方位信息,，實現(xiàn)多模態(tài)交互,，已成為遠程會議系統(tǒng)的重要語音前端[4-5]。
