Palestinian Arabic regional accent recognition

Abualsoud Hanani, H. Basha, Y. Sharaf, Stephen Eugene Taylor
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引用次数: 10

Abstract

We attempt to automatically recognize the speaker's accent among regional Arabic Palestinian accents from four different regions of Palestine, i.e. Jerusalem (JE), Hebron (HE), Nablus (NA) and Ramallah (RA). To achieve this goal, we applied the state of the art techniques used in speaker and language identification, namely, Gaussian Mixture Model - Universal Background Model (GMM-UBM), Gaussian Mixture Model - Support Vector Machines (GMM-SVM) and I-vector framework. All of these systems were trained and tested on speech of 200 speakers. GMM-SVM and I-vector systems outperformed the baseline GMM-UBM system. The best result (accuracy of 81.5%) was obtained by an I-vector system with 64 Gaussian components, compared to an accuracy of 73.4% achieved by human listeners on the same testing utterances.
巴勒斯坦阿拉伯地区口音识别
我们试图从巴勒斯坦四个不同地区的阿拉伯巴勒斯坦口音中自动识别说话者的口音,即耶路撒冷(JE),希伯伦(HE),纳布卢斯(NA)和拉马拉(RA)。为了实现这一目标,我们应用了说话人和语言识别中使用的最先进技术,即高斯混合模型-通用背景模型(GMM-UBM),高斯混合模型-支持向量机(GMM-SVM)和i -向量框架。所有这些系统都在200名说话者的讲话上进行了训练和测试。GMM-SVM和I-vector系统优于基线GMM-UBM系统。具有64个高斯分量的i向量系统获得了最好的结果(准确率为81.5%),相比之下,人类听者在相同的测试话语上的准确率为73.4%。
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