Knowledge Commons of Institute of Automation,CAS
Interference robust DOA estimation of human speech by exploiting historical information and temporal correlation | |
Xue, Wei; Liang, Shan; Liu, Wenju | |
2013 | |
会议名称 | the Annual Conference of the International Speech Communication Association, INTERSPEECH |
会议录名称 | Annual Conference of the International Speech Communication Association (INTERSPEECH) |
页码 | 2895-2899 |
会议日期 | 2013 |
会议地点 | Lyon, France |
摘要 | Although various DOA estimation methods for human speech have been presented, most of them assume noises received by different microphones are undirected. However, strong directional interferences often also exist in practical scenarios and the performances of existing methods degrade seriously in such case. In this paper, we present a new interference robust DOA estimation method for human speech. Historical information and temporal correlation are taken advantage to deal with the problem. Firstly, utilizing the historical DOA estimates, we perform “post-beamforming” in the last frame to suppress the directional interferences. Then exploiting temporal correlation of speech spectra, frequency weights which highlight the effects of speech frequency bins are calculated based on the estimated a priori SNR of enhanced signal. Finally, we propose a new DOA cost function using frequency-weighted spatial correlation matrix to estimate the DOA of speech source. Experimental results show that the proposed method outperforms existing algorithms in reverberant environments with additive white Gaussian noises in the presence of different kinds of interferences. |
关键词 | Direction Of Arrival Estimation Microphone Array Signal Processing Directional Noise |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/4314 |
专题 | 多模态人工智能系统全国重点实验室_机器人视觉 |
作者单位 | National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences |
第一作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Xue, Wei,Liang, Shan,Liu, Wenju. Interference robust DOA estimation of human speech by exploiting historical information and temporal correlation[C],2013:2895-2899. |
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