Ensemble based speaker verification using adapted score fusion in noisy reverberant environments
Ensemble based speaker verification using adapted score fusion in noisy reverberant environments
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DOI：
10.1109/apsipa.2016.7820794
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发表时间：
2016-12
期刊：
影响因子：
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通讯作者：
Ryosuke Nakanishi;Sayaka Shiota;H. Kiya
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文献类型：
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作者：
Ryosuke Nakanishi;Sayaka Shiota;H. Kiya
提出了一种基于合奏的混响环境下自适应乐谱融合的自动说话人识别方法。众所周知，背景噪声和混响会影响ASV系统的性能。为了提高系统对噪声和混响的鲁棒性，已有多种方法被报道，其中基于集成的方法是在噪声环境下的有效方法之一。基于集成的方法使用多个弱学习器的组合来获得比单个学习器方法更高的性能。然而，由于其性能取决于融合权值，因此需要适当的权值估计方法。提出了一种基于监督自适应和进化更新算法的权重估计方法。在我们的实验中，我们使用了最近发表的QUT-NOISE-SRE协议来模拟干净语音的混响。实验结果表明了QUT-NOISE-SRE协议的特点以及该方法在噪声混响环境下的有效性。
This paper proposes an ensemble based automatic speaker recognition (ASV) using adapted score fusion in noisy reverberant environment. It is well known that background noise and reverberation affect the performance of the ASV systems. Various techniques have been reported to improve the robustness against noise and reverberation, and an ensemble based method is one of the effective techniques in the noisy environment. The ensemble based method uses a combination of several weak learners to achieve higher performance than a single learner method. However, since the performance is depended on the fusion weights, the adequate weight estimation method is required. The proposed weight estimation method is based a supervised adaptation and the evolutionary update algorithm. The QUT-NOISE-SRE protocol, which has been published recently, is used for simulating the reverberation of the clean speech in our experiments. The experimental results report the characteristics of the QUT-NOISE-SRE protocol and the effectiveness of the proposed method in noisy reverberant environment.