| Budget Amount *help |
¥17,160,000 (Direct Cost: ¥13,200,000、Indirect Cost: ¥3,960,000)
Fiscal Year 2020: ¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
Fiscal Year 2019: ¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
Fiscal Year 2018: ¥4,680,000 (Direct Cost: ¥3,600,000、Indirect Cost: ¥1,080,000)
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| Outline of Final Research Achievements |
We have proposed a novel framework called Neuro-SERKET as a distributed development framework to develop a self-organizing cognitive architecture that can utilize the advantages of both probabilistic generative models and deep learning. The Neuro-SERKET is an extension of the previously proposed framework, SERKET. This enables us to integrate (deep) probabilistic generative models that have been developed in a distributed manner and to reason about them as a whole. We also have studied the fusion of SLAM and GAN, and the fusion of deep generative models for speech conversion and probabilistic generative models for speech recognition. Through these studies, we built the foundation of a self-organizing cognitive architecture.
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