1 research outputs found
On the Correlation of Context-Aware Language Models With the Intelligibility of Polish Target Words to Czech Readers
This contribution seeks to provide a rational probabilistic explanation for the intelligibility
of words in a genetically related language that is unknown to the reader, a phenomenon
referred to as intercomprehension. In this research domain, linguistic distance, among
other factors, was proved to correlate well with the mutual intelligibility of individual words.
However, the role of context for the intelligibility of target words in sentences was subject
to very few studies. To address this, we analyze data from web-based experiments in
which Czech (CS) respondents were asked to translate highly predictable target words at
the final position of Polish sentences. We compare correlations of target word intelligibility
with data from 3-g language models (LMs) to their correlations with data obtained from
context-aware LMs. More specifically, we evaluate two context-aware LM architectures:
Long Short-Term Memory (LSTMs) that can, theoretically, take infinitely long-distance
dependencies into account and Transformer-based LMs which can access the whole
input sequence at the same time. We investigate how their use of context affects surprisal
and its correlation with intelligibility