Human-like general language processing
- URL: http://arxiv.org/abs/2005.09175v2
- Date: Fri, 29 May 2020 08:08:02 GMT
- Title: Human-like general language processing
- Authors: Feng Qi, Guanjun Jiang
- Abstract summary: We propose a human-like general language processing architecture, which contains sensorimotor, association, and cognitive systems.
The HGLP network learns from easy to hard like a child, understands word meaning by coactivating multimodal neurons, comprehends and generates sentences by real-time constructing a virtual world model.
HGLP rapidly learned 10+ different tasks including object recognition, sentence comprehension, imagination, attention control, query, inference, motion judgement, mixed arithmetic operation, digit tracing and writing, and human-like iterative thinking process guided by language.
- Score: 0.6510507449705342
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Using language makes human beings surpass animals in wisdom. To let machines
understand, learn, and use language flexibly, we propose a human-like general
language processing (HGLP) architecture, which contains sensorimotor,
association, and cognitive systems. The HGLP network learns from easy to hard
like a child, understands word meaning by coactivating multimodal neurons,
comprehends and generates sentences by real-time constructing a virtual world
model, and can express the whole thinking process verbally. HGLP rapidly
learned 10+ different tasks including object recognition, sentence
comprehension, imagination, attention control, query, inference, motion
judgement, mixed arithmetic operation, digit tracing and writing, and
human-like iterative thinking process guided by language. Language in the HGLP
framework is not matching nor correlation statistics, but a script that can
describe and control the imagination.
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