Learning the mapping from surface to underlying representations in an artificial language
Learning the mapping from surface to underlying representations in an artificial language
复制标题
用人工语言学习从表面到底层表示的映射
DOI:
--
复制
发表时间:
2006
期刊:
影响因子:
--
通讯作者:
Emmanuel Dupoux
中科院分区:
文献类型:
--
作者:
S. Peperkamp;Emmanuel Dupoux
When infants acquire their native language they not only extract languagespecific segmental categories and the words of their language, they also learn the underlying form of these words. This is difficult because words can have multiple phonetic realizations, according to the phonological context. In a series of artificial language-learning experiments with a phrase-picture matching task, we consider the respective contributions of word meaning and distributional information for the acquisition of underlying representations in the presence of an allophonic rule. We show that on the basis of semantic information, French adults can learn to map voiced and voiceless stops or fricatives onto the same underlying phonemes, whereas in their native language voicing is phonemic in all obstruents. They do not extend this knowledge to novel stops or fricatives, though. In the presence of distributional cues only, learning is much reduced and limited to the words subjects are trained on. We also test if phonological naturalness plays a role in this type of learning, and find that if semantic information is present, French adults can learn to map different segments onto a single underlying phoneme even if the mappings are highly unnatural. We discuss our findings in light of current statistical learning approaches to language acquisition.
DOI:
10.1037/0096-1523.20.2.421
发表时间:
1994-04-01
影响因子:
2.1
作者:
POLKA, L;WERKER, JF
通讯作者:
WERKER, JF
影响因子:
56.9
作者:
KUHL, PK;WILLIAMS, KA;LINDBLOM, B
通讯作者:
LINDBLOM, B
影响因子:
4
作者:
Saffran, JR;Thiessen, ED
通讯作者:
Thiessen, ED