In real applications, environmental effects such as additive noise and room reverberation lead to a mismatch between training and testing signals that substantially reduces the performance of far-field speaker identification. As a solution to this mismatch problem, in this paper, a new binaural speaker identification system is proposed which employs the well-known equalization-cancelation technique in its structure. The equalization-cancelation algorithm is employed to enhance the input test speech and alleviate the detrimental effects of noise and reverberation in the speaker identification system. The performance of the proposed speaker identification system is compared with unprocessed identification systems and a traditional binaural speaker identification system from the literature. The proposed system is evaluated in both anechoic and reverberant conditions using different types of noise at various azimuthal positions. Simulation results show the superiority of the proposed method in all experimental conditions.

中文翻译：

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使用均衡消除技术的双耳说话人识别

在实际应用中，加性噪声和房间混响等环境影响会导致训练和测试信号之间的不匹配，从而大大降低远场说话人识别的性能。为了解决这个不匹配问题，本文提出了一种新的双耳说话人识别系统，该系统在其结构上采用了众所周知的均衡抵消技术。采用均衡-消除算法来增强输入测试语音，减轻说话人识别系统中噪声和混响的不利影响。将所提出的说话人识别系统的性能与未处理的识别系统和文献中的传统双耳说话人识别系统进行了比较。所提出的系统在无回声和混响条件下使用不同方位角位置的不同类型的噪声进行评估。仿真结果表明了该方法在所有实验条件下的优越性。