Age and Gender Classification for a Home-Robot Service

This paper describes a method to recognize the age and gender of a user on the basis of human speech. Using voice source characteristics of the Mel frequency cepstral coefficients (MFCCs), a Gaussian mixture model (GMM) technique is applied in an effort to discover the age, gender, and other informa...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Hye-Jin Kim, Kyungsuk Bae, Ho-Sub Yoon
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Application software Cellular phones Cognitive robotics Human robot interaction Jitter Mel frequency cepstral coefficient Senior citizens Speech analysis Speech recognition Testing
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