| Autor: |
Alejandrina Cristia, Emmanuel Dupoux, Nan Bernstein Ratner, Melanie Soderstrom |
| Jazyk: |
angličtina |
| Rok vydání: |
2019 |
| Předmět: |
|
| Zdroj: |
Open Mind, Vol 3, Pp 13-22 (2019) |
| Druh dokumentu: |
article |
| ISSN: |
2470-2986 |
| DOI: |
10.1162/opmi_a_00022 |
| Popis: |
Previous computational modeling suggests it is much easier to segment words from child-directed speech (CDS) than adult-directed speech (ADS). However, this conclusion is based on data collected in the laboratory, with CDS from play sessions and ADS between a parent and an experimenter, which may not be representative of ecologically collected CDS and ADS. Fully naturalistic ADS and CDS collected with a nonintrusive recording device as the child went about her day were analyzed with a diverse set of algorithms. The difference between registers was small compared to differences between algorithms; it reduced when corpora were matched, and it even reversed under some conditions. These results highlight the interest of studying learnability using naturalistic corpora and diverse algorithmic definitions. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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