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The Meta-Pi Network

其他書名	Building Distributed Knowledge Representations for Robust Pattern Recognition
出版	Carnegie Mellon University, Computer Science Department, 1989
URL	http://books.google.com.hk/books?id=tEblGwAACAAJ&hl=&source=gbs_api

註釋We demonstrate the Meta-Pi architecture's performance in the context of multi-speaker phoneme recognition. In this task the Meta-Pi superstructure integrates conflict-arbitrated Time-Delay Neural Network (TDNN) sub-networks to perform multi-speaker phoneme recognition at speaker-dependent rates. It achieves a 6-speaker (4 males, 2 females) recognition rate of 98.4% on a database of voiced-stops (/b, d, g/). This recognition performance constitutes a significant improvement over the 95.9% multi-speaker recognition rate obtained by a single TDNN trained in multi-speaker fashion. It also approaches the 98.7% average of the speaker-dependent recognition rates for the six speakers processed. We show that the Meta-Pi network can learn--without direct supervision--to recognize the speech of one particular speaker using a dynamic combination of internal models of other speakers exclusively (99.8% correct). The Meta-Pi model constitutes a viable basis for connectionist pattern recognition systems that can rapidly adapt to new stimuli by using dynamic, conditional combinations of existing stimulus-specific models."