Paper Info
Title
Age and Gender Classification for a Home-Robot Service
Abstract
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 information as regards a user. On the basis of this information, service applications for robots can satisfy users by offering services adaptive to the special needs of specific user groups that may include adults and children as well as females and males. The major aim of this paper is to discover the voice source parameters of age and gender and to classify these two characteristics simultaneously. ETRI-VoiceDB2006 was employed to evaluate the proposed method.
Year
DOI
Venue
2007
10.1109/ROMAN.2007.4415065
RO-MAN
Keywords
Field
DocType
robots,speech recognition,voice source characteristics,home-robot service,human speech,speech-based user interfaces,etri-voicedb2006,cepstral analysis,gender classification,age classification,gaussian processes,gaussian mixture model,mel frequency cepstral coefficients,mel frequency cepstral coefficient,satisfiability
Home robot,Mel-frequency cepstrum,Special needs,Pattern recognition,Computer science,Voice activity detection,Speech recognition,Gaussian process,Artificial intelligence,Voice source,Robot,Mixture model
Conference
ISBN
Citations 
PageRank 
978-1-4244-1635-6
7
0.56
References 
Authors
4
3
Name
Order
Citations
PageRank
Hye-Jin Kim1276.58
Kyung-suk Bae281.29
Ho-sub Yoon3383.28