Tetsuya Ogata

Paired Recurrent Autoencoders for Bidirectional Translation Between Robot Actions and Linguistic Descriptions

2018 · IEEE Robotics and Automation Letters

We propose a novel deep learning framework for bidirectional translation between robot actions and their linguistic descriptions. Our model consists of two recurrent autoencoders (RAEs). One RAE learns to encode action sequences as fixed-dimensional vectors …