Presentation 1996/11/21
Concept Acquisition from Multiple Information Sources by the EM Algorithm
Shotaro Akaho, Osamu Hasegawa, Takashi Yoshimura, Hideki Asoh, Satoru Hayamizu,
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Abstract(in English) We consider a framework of concept learning where information from multiple sources such as images and speech are integrated. From the training data where one of the properties of each image is shown by speech, the system acquire the classification of properties automatically. We propose multi-resolution higher order autocorrelation features, and extract information which is necessary for concept acquisition by the canonical correlation analysis between image features and speech features. In the final stage, we propose multiple value regression model as a concept acquisition model, where the parameters can be estimated by the EM algorithm. We also show some experimental results.
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Keyword(in English) EM algorithm / multiple information / concept acquisition / canonical correlation analysis
Paper # PRMU96-91
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Conference Information
Committee PRMU
Conference Date 1996/11/21(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Concept Acquisition from Multiple Information Sources by the EM Algorithm
Sub Title (in English)
Keyword(1) EM algorithm
Keyword(2) multiple information
Keyword(3) concept acquisition
Keyword(4) canonical correlation analysis
1st Author's Name Shotaro Akaho
1st Author's Affiliation Electrotechnical Laboratory()
2nd Author's Name Osamu Hasegawa
2nd Author's Affiliation Electrotechnical Laboratory
3rd Author's Name Takashi Yoshimura
3rd Author's Affiliation Electrotechnical Laboratory
4th Author's Name Hideki Asoh
4th Author's Affiliation Electrotechnical Laboratory
5th Author's Name Satoru Hayamizu
5th Author's Affiliation Electrotechnical Laboratory
Date 1996/11/21
Paper # PRMU96-91
Volume (vol) vol.96
Number (no) 384
Page pp.pp.-
#Pages 8
Date of Issue