Electroencephalography (EEG) dataset during naturalistic music listening comprising different genres with familiarity and enjoyment ratings.

The article provides an open-source Music Listening- Genre (MUSIN-G) EEG dataset which contains 20 participants' continuous Electroencephalography responses to 12 songs of different genres (from Indian folk music to Goth Rock to western electronic), along with their familiarity and enjoyment ratings. The participants include 16 males and 4 females, with an average age of 25.3 (+/-3.38). The EEG data was collected at the Indian Institute of Technology Gandhinagar, India, using 128 channels Hydrocel Geodesic Sensor Net (HCGSN) and the Netstation 5.4 data acquiring software. We provide the raw and partially preprocessed data of each participant while they listened to 12 different songs with closed eyes. The dataset also contains the behavioural familiarity and enjoyment ratings (scale of 1 to 5) of the participants for each of the songs. In this article, we further discuss the preprocessing steps which can be used on the dataset and prepare the data for analysis, as in the paper [1].

Resonance as a Design Strategy for AI and Social Robots.

Resonance, a powerful and pervasive phenomenon, appears to play a major role in human interactions. This article investigates the relationship between the physical mechanism of resonance and the human experience of resonance, and considers possibilities for enhancing the experience of resonance within human-robot interactions. We first introduce resonance as a widespread cultural and scientific metaphor. Then, we review the nature of "sympathetic resonance" as a physical mechanism. Following this introduction, the remainder of the article is organized in two parts. In part one, we review the role of resonance (including synchronization and rhythmic entrainment) in human cognition and social interactions. Then, in part two, we review resonance-related phenomena in robotics and artificial intelligence (AI). These two reviews serve as ground for the introduction of a design strategy and combinatorial design space for shaping resonant interactions with robots and AI. We conclude by posing hypotheses and research questions for future empirical studies and discuss a range of ethical and aesthetic issues associated with resonance in human-robot interactions.