Paper: Learning Words and Their Meanings from Unsegmented Child-directed Speech

ACL ID N10-1074
Title Learning Words and Their Meanings from Unsegmented Child-directed Speech
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

Most work on language acquisition treats word segmentation—the identification of lin- guistic segments from continuous speech— and word learning—the mapping of those seg- ments to meanings—as separate problems. These two abilities develop in parallel, how- ever, raising the question of whether they might interact. To explore the question, we present a new Bayesian segmentation model that incorporates aspects of word learning and compare it to a model that ignores word mean- ings. The model that learns word meanings proposes more adult-like segmentations for the meaning-bearing words. This result sug- gests that the non-linguistic context may sup- ply important information for learning word segmentations as well as word meanings.