Think Fast: Rapid Localization of Teleoperator Gaze in 360° Hosted Telepresence

We evaluate the ability of locally present participants to localize an avatar head’s gaze direction rapidly in hosted telepresence. We performed a controlled user study to test two potential solutions to indicate a remote user’s gaze. We analyze the influence of the user’s distance to the avatar and display technique on localization accuracy. Furthermore, we examine the effect of the avatar head’s rotation around the pitch and yaw axes on the localization accuracy. Our experimental results suggest that all these factors have a significant effect on the localization accuracy with different extent. The results also verified that people had a better perceptive and localizing ability when interacting with a 3D AR-displayed avatar. In addition, participants preferred to interact with a 3D avatar displayed using a simulated AR technique instead of with a 2D avatar displayed in a tablet because of its high realism. Our findings motivate the need for 3D avatar display in the further design of telepresence systems.

Distant Speaker Recognition: An Overview

Distant speaker recognition (DSR) system assumes the microphones are far away from the speaker’s mouth. Also, the position of microphones can vary. Furthermore, various challenges and limitation in terms of coloration, ambient noise and reverberation can bring some difficulties for recognition of the speaker. Although, applying speech enhancement techniques can attenuate speech distortion components, it may remove speaker-specific information and increase the processing time in real-time application. Currently, many efforts have been investigated to develop DSR for commercial viable systems. In this paper, state-of-the-art techniques in DSR such as robust feature extraction, feature normalization, robust speaker modeling, model compensation, dereverberation and score normalization are discussed to overcome the speech degradation components i.e., reverberation and ambient noise. Performance results on DSR show that whenever speaker to microphone distant increases, recognition rates decreases and equal error rate (EER) increases. Finally, the paper concludes that applying robust feature and robust speaker model varying lesser with distant, can improve the DSR performance.

Importance of Touch for Conveying Affection in a Multimodal Interaction with a Small Humanoid Robot

To be accepted as a part of our everyday lives, companion robots will require the capability to communicate socially, recognizing people's behavior and responding appropriately. In particular, we hypothesized that a humanoid robot should be able to recognize affectionate touches conveying liking or dislike because (a) a humanoid form elicits expectations of a high degree of social intelligence, (b) touch behavior plays a fundamental and crucial role in human bonding, and (c) robotic responses providing affection could contribute to people's quality of life. The hypothesis that people will seek to affectionately touch a robot needed to be verified because robots are typically not soft or warm like humans, and people can communicate through various other modalities such as vision and sound. The main challenge faced was that people's social norms are highly complex, involving behavior in multiple channels. To deal with this challenge, we adopted an approach in which we analyzed free interactions and also asked participants to rate short video-clips depicting human–robot interaction. As a result, we verified that touch plays an important part in the communication of affection from a person to a humanoid robot considered capable of recognizing cues in touch, vision, and sound. Our results suggest that designers of affectionate interactions with a humanoid robot should not ignore the fundamental modality of touch.