Technical Name 多AI模型整合的導盲對話系統
Project Operator National Central University
Project Host 陳慶瀚
The dialogue system is the main subsystem of the visually impaired navigation system, which provides destinations for the navigation system through multiple dialogues. We use the knowledge graph as the basis for reasoning. In terms of close-range navigation, deep learning technology is used to develop RGB camera detection depth algorithm, indoor semantic cutting algorithm, integrated detection depth estimationindoor semantic cutting in indoor obstacle avoidance, etc. The whole system uses the CellS software design framework to integrate distributed AIoT systems.
Scientific Breakthrough
This technology integrates semantic recognition into the dialogue system,implements a dialogue system based on the knowledge graph as the basis for reasoning. Unsupervised neural network is used to classify the knowledge graph,then deep neural network is used for semantic recognition. In the MQTT architecture, CellS is used to implement the dialogue engineapplied to multi-AI model control. Performance experiments show that our application can be accelerated up to 1.94 times.
Industrial Applicability
This technology is applicable to all human-computer interaction systems that require voice-triggered activation, such as popular voice assistant products such as Google Assistant, Apple's Siri, Microsoft's Cortana,Amazon's Alex. In addition to improving the security of the system, the low computational complexitymemory requirement are more conducive to achieving low power, low cost microcontroller-based product design.
Matching Needs
Keyword Dialogue system Knowledge base Visually Impaired Navigation Deep learning AIoT Road recognition Sign recognition Distributional computing AI model integration Computer vision
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