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Conference Paper Multi-Modal Fusion of Speech-Gesture Using Integrated Probability Density Distribution
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Authors
Chi-Geun Lee, Mun-Sung Han
Issue Date
2008-12
Citation
International Symposium on Intelligent Information Technology Application (IITA) 2008, pp.361-364
Language
English
Type
Conference Paper
DOI
https://dx.doi.org/10.1109/IITA.2008.278
Abstract
Although speech recognition has been explored extensively and successfully developed, it still encounters serious errors in noisy environments. In such cases, gestures, a by-product of speech, can be used to help interpret the speech. In this paper, we propose a method of multi-modal fusion recognition of speech-gesture using integrated discrete probability density function omit estimated by a histogram. The method is tested with a microphone and a 3-axis accelerator in a real-time experiment. The test has two parts : a method of add-and-accumulate speech and gesture probability density functions respectively, and a more complicated method of creating new probability density function from integrating the two PDF's of speech and gesture. © 2008 IEEE.
KSP Keywords
By-products, Fusion recognition, Probability Density Function, Probability density distribution, multimodal fusion, noisy environments, real-time experiment, speech recognition