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Robots Learn Language Via Random Syllabic Babble
By speaking with a robot as if it was a small child, the robot was able to evolve its use of sounds from random syllabic babble to producing some salient wordforms, the names of simple shapes and colors.
The participants were not researchers; they used their own words, rather than any prescribed lines.
The researchers, led by Caroline Lyon of the University of Hertfordshire, suggest that this work may be useful for understanding language acquisition in humans. "It is known that infants are sensitive to the frequency of sounds in speech, and these experiments show how this sensitivity can be modelled and contribute to the learning of word forms by a robot."
(The scenario for the human-robot dialogue)
Our work focuses on early stages analogous to some characteristics of a human child of about 6 to 14 months, the transition from babbling to first word forms. We investigate one mechanism among many that may contribute to this process, a key factor being the sensitivity of learners to the statistical distribution of linguistic elements. As well as being necessary for learning word meanings, the acquisition of anchor word forms facilitates the segmentation of an acoustic stream through other mechanisms. In our experiments some salient one-syllable word forms are learnt by a humanoid robot in real-time interactions with naive participants. Words emerge from random syllabic babble through a learning process based on a dialogue between the robot and the human participant, whose speech is perceived by the robot as a stream of phonemes....word forms are usually produced by the robot after a few minutes of dialogue, employing a simple, real-time, frequency dependent mechanism. This work shows the potential of human-robot interaction systems in studies of the dynamics of early language acquisition.
Perhaps readers can think of a better example of robot learning in science fiction; I was thinking of the learning robots from the 1960 short story Callahan and the Wheelies by Stephen Barr.
Via Interactive Language Learning by Robots via EurekAlert.
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