Infants learn to segment words from fluent speech during the same period as they learn native language phonetic categories, yet accounts of phonetic category acquisition typically ignore information about the words in which sounds appear. This work uses computational and behavioral methods to explore the hypothesis that the words infants segment from fluent speech can provide useful cues to guide phonetic category acquisition. An interactive Bayesian learning model is created to illustrate how feedback from segmented words might constrain phonetic category learning by providing information about which sounds occur together in words. This model is compared with two models that learn phonetic categories only from distributions of sounds in acoustic space. Simulations show that word-level information can successfully disambiguate overlapping English vowel categories, leading to more robust category learning than distributional information alone. Next, two experiments test whether human learners can make use of the word-level cues required for this type of interactive learning. These experiments demonstrate that adult learners are sensitive to cooccurrence patterns of sounds in acoustic word tokens of an unfamiliar language. However, human learners appear to treat the patterns differently when words are heard in isolation versus when they are heard in fluent speech, adopting either a word-level or a phonological interpretation depending on experimental context. These behavioral results partially support the predictions of the model but underscore the complexity of the phonetic category learning problem. Together, the computational and behavioral results suggest that phonetic category learning can be better understood in conjunction with other contemporaneous learning processes and that simultaneous learning of multiple layers of linguistic structure can potentially make the language acquisition problem more tractable.
Feldman, Naomi H.,
"Interactions between word and speech sound categorization in language acquisition"
(2011).
Cognitive Sciences Theses and Dissertations.
Brown Digital Repository. Brown University Library.
https://doi.org/10.7301/Z00P0X95
