球谐域自适应混响抵消与声源定位算法
Dereverberation and localization using adaptive reverberation cancellation in the spherical harmonic domain
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摘要: 提出了一种基于球谐域的自适应混响抵消与声源定位算法,该方法通过去混响处理改善语音质量,并提高球谐域定位算法在混响环境下的定位性能。推导了基于多通道线性预测的自适应混响抵消算法在球谐域的表达式,针对刚球模型提出分阶处理的去混响方法,并对去混响后的信号进行波达方向估计。采用32元球阵的仿真结果表明,相比于球谐域不分阶去混响方法,该方法最大可减少约2/3的运算量,同时语音PESQ得分及SRMR均显著提高。利用实验数据对算法性能进行测试,实验结果验证了该方法在实际声学环境中去混响和声源定位的有效性。Abstract: A dereverberation and localization approach is proposed to improve speech quality and performance of localization of sound sources in reverberant environments,which is based on adaptive reverberation cancellation in the spherical harmonic domain.First,we propose an adaptive reverberation cancellation method based on multi-channel linear prediction in the spherical harmonic domain.Then,for different spherical harmonic orders,dereverberation methods are designed separately using a rigid spherical array and the dereverberated signal is further applied for localization.By using a 32-channel spherical microphone array,simulation results show that compared with the traditional dereverberation algorithm in the spherical harmonic domian,the proposed approach can reduce up to 2/3 computational complexity,as well as significantly improving the PESQ score and SRMR.Experiments in a reverberant room confirm the validity of the proposed method in terms of dereverberation and localization.