title: Cognitive Bias for Learning Speech Sounds From a Continuous Signal Space Seems Nonlinguistic.
abstract: When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults' generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants' reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories.
authors.affiliation: Artificial Intelligence Lab, Vrije Universiteit Brussel, Belgium.
authors.forename: Sabine
authors.initials: S
authors.lastname: van der Ham
authors.affiliation: Artificial Intelligence Lab, Vrije Universiteit Brussel, Belgium.
authors.forename: Bart
authors.initials: B
authors.lastname: de Boer
keywords: continuous signal space; evolution of speech; frequency learning; learning biases; perception bias