Robots Learning to Say `No': Prohibition and Rejective Mechanisms in Acquisition of Linguistic Negation
This addresses the challenge of grounding linguistic negation in AI and robotics, offering insights into early language acquisition, though it is incremental in exploring social and affective mechanisms.
The study investigated how a child-like robot learns the word 'no' through social interaction, finding that prosodic salience in prohibitive utterances and negative affective states facilitate its acquisition, but Hebbian-type algorithms may be unsuitable for grounding such non-referential words.
`No' belongs to the first ten words used by children and embodies the first active form of linguistic negation. Despite its early occurrence the details of its acquisition process remain largely unknown. The circumstance that `no' cannot be construed as a label for perceptible objects or events puts it outside of the scope of most modern accounts of language acquisition. Moreover, most symbol grounding architectures will struggle to ground the word due to its non-referential character. In an experimental study involving the child-like humanoid robot iCub that was designed to illuminate the acquisition process of negation words, the robot is deployed in several rounds of speech-wise unconstrained interaction with naïve participants acting as its language teachers. The results corroborate the hypothesis that affect or volition plays a pivotal role in the socially distributed acquisition process. Negation words are prosodically salient within prohibitive utterances and negative intent interpretations such that they can be easily isolated from the teacher's speech signal. These words subsequently may be grounded in negative affective states. However, observations of the nature of prohibitive acts and the temporal relationships between its linguistic and extra-linguistic components raise serious questions over the suitability of Hebbian-type algorithms for language grounding.