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Synthesized speech technology holds potential for enabling natural conversations between humans and machines, particularly in social robotics. However, the combination of synthesized speech with social robots still lacks some qualities of natural speech, which is crucial for human robot interactions, especially for children. In this study, we recorded the neural activity of 5-year-old, typically developing children from middle to high socio-economic households using EEG while they listened to stories narrated by either an adult or a social robot, specifically Furhat. We measured cortical speech tracking to compare how well children's brains tracked synthesized speech from a robot compared to natural speech from an adult. Our results suggest that children do indeed show cortical speech tracking in both scenarios. The results also suggest that cortical speech tracking requires larger time delays between the speech and the response to reach its peak in child-robot interaction compared to child-adult interaction. Possible sources of these differences along with their implications are discussed.

While previous studies highlight the role that children’s interest in natural categories predict their learning of new label-object associations in these categories, the long-term implications of such a relationship – the extent to which children’s interest shape lexical development – remain unclear. The current study examines whether children’s interests in different natural object categories predict their subsequent interest and the number of words children know in those categories six months later. Using data from sixty-seven children tested at eighteen and twenty-four months of age, we found that parents’ estimates of interest in natural object categories at 18-months predicted their reports of their child’s interests at 24-months. Parent interest reports at 18-months also predicted the number of words that children are reported to know in that category at 24-months. Taken together, this study documents the longitudinal relationship between children’s interests, parents’ awareness of their children’s interests and later vocabulary development.

Research on whether asexual individuals desire (romantic) relationships, and if so, how they picture their ideal relationship has been growing in the past years. However, less is known about the preferred attributes of an ideal partner in such relationships and whether these partner(ship) preferences are different from what heterosexual individuals want. The goal of the present study was to compare the types of preferred relationships and the ideal characteristics of a long-term partner of self-identified asexual and heterosexual women. Additionally, we examined differences in characteristics of asexual and heterosexual women using self-evaluations of the same attributes used for the partner preference ratings. We used data from the Ideal Partner Survey, a large-scale, multinational online study. Of 51,775 participants, 51,328 identified as heterosexual (Mage = 25.13) and 447 identified as asexual (Mage = 24.03). To create comparable samples for analyses, each asexual person was matched with a heterosexual person using propensity score matching (relationship options sample = 646, partner preference sample = 780, self-rating sample = 772). Compared to heterosexual women, asexual women were less interested in purely sexual relationships, and more interested in emotionally romantic and alternative types of committed relationships as well as not being in any relationship (“single”). Asexual women placed less importance on all partner preference attributes, except educated and intelligent. They also consistently rated themselves lower on all attributes than heterosexual women. These findings suggest distinct differences between asexual and heterosexual women in their relationship interests, partner preferences, and self-perceived characteristics.