Age and gender recognition for telephone applications based on GMM supervectors and support vector machines

机译：基于GMM超向量和支持向量机的电话应用程序的年龄和性别识别

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This paper compares two approaches of automatic age and gender classification with 7 classes. The first approach are Gaussian mixture models (GMMs) with universal background models (UBMs), which is well known for the task of speaker identification/verific

机译：本文比较了7种类别的自动年龄和性别分类的两种方法。第一种方法是具有通用背景模型（UBM）的高斯混合模型（GMM），以说话人识别/验证的任务而闻名

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来源
《Personal, Indoor and Mobile Radio Communications,2005 IEEE 16th International Symposium on》|2008年|P.1605-1608|共4页
会议地点 Las Vegas,NV
作者
Bocklet; T.; Maier; A.; Bauer; J.G.; Burkhardt; F.; Noth; E.;
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Gaussian processes; Karhunen-Loeve transforms; acoustic signal processing; expectation-maximisation algorithm; gender issues; polynomials; radial basis function networks; speaker recognition; support vector machines; Gaussian mixture model supervectors; KL diverge;

机译：高斯过程； Karhunen-Loeve变换；声音信号处理；期望最大化算法；性别问题;多项式径向基函数网络；说话人识别；支持向量机；高斯混合模型超向量；吉隆坡分歧;

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3. Support vector machines using GMM supervectors for speaker verification [J] . Campbell W.M., Sturim D.E., Reynolds D.A. IEEE signal processing letters . 2006,第5期

机译：使用GMM超向量的支持向量机用于说话人验证
4. Age and gender recognition for telephone applications based on GMM supervectors and support vector machines [C] . Bocklet T., Maier A., Bauer J.G., IEEE International Conference on Acoustics, Speech and Signal Processing . 2008

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7. Age and Gender Recognition for Telephone Applications based on GMM Supervectors and Support Vector Machines [O] . Tobias Bocklet, Andreas Maier, Josef G. Bauer, 2008

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8. Face Recognition with Support Vector Machines: Global versus Component- Based Approach [R] . Heisele, B. , Ho, P. , Poggio, T. 2001

机译：支持向量机的人脸识别：全局与基于组件的方法

Age and gender recognition for telephone applications based on GMM supervectors and support vector machines

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