This paper proposes a novel Generative Adversarial Network (GAN)-based strategy to augment subjective haptic Quality of Experience (QoE) datasets for bilateral teleoperation with haptic feedback without conducting time-consuming subjective experiments. In our previous work, we proposed a multi-assessment fusion approach to predict subjective haptic quality using a collection of objective metrics. This method requires a sufficiently large haptic dataset with QoE labels.
