A Language-agnostic Model of Child Language Acquisition
This is an incremental study addressing language acquisition modeling for Hebrew, highlighting challenges in cross-linguistic transfer.
The authors adapted an existing semantic bootstrapping model for child language acquisition from English to Hebrew, finding that it transferred mostly but learned slower and less robustly due to Hebrew's richer morphology.
This work reimplements a recent semantic bootstrapping child-language acquisition model, which was originally designed for English, and trains it to learn a new language: Hebrew. The model learns from pairs of utterances and logical forms as meaning representations, and acquires both syntax and word meanings simultaneously. The results show that the model mostly transfers to Hebrew, but that a number of factors, including the richer morphology in Hebrew, makes the learning slower and less robust. This suggests that a clear direction for future work is to enable the model to leverage the similarities between different word forms.