This paper investigates the processes in comprehending spoken noun-noun
compounds, using data from the BALDEY database. BALDEY contains lexicality
judgments and reaction times (RTs) for Dutch stimuli for which also
linguistic information is included. Two different approaches are combined.
The first is based on regression by Dynamic Survival Analysis, which
models decisions and RTs as a consequence of the fact that a cumulative
density function exceeds some threshold. The parameters of that function
are estimated from the observed RT data. The second approach is based
on DIANA, a process-oriented computational model of human word comprehension,
which simulates the comprehension process with the acoustic stimulus
as input. DIANA gives the identity and the number of the word candidates
that are activated at each 10 ms time step.
Both approaches show
how the processes involved in comprehending compounds change during
a stimulus. Survival Analysis shows that the impact of word duration
varies during the course of a stimulus. The density of word and non-word
hypotheses in DIANA shows a corresponding pattern with different regimes.
We show how the approaches complement each other, and discuss additional
ways in which data and process models can be combined.
Cite as: Bosch, L.t., Boves, L., Ernestus, M. (2017) The Recognition of Compounds: A Computational Account. Proc. Interspeech 2017, 1158-1162, doi: 10.21437/Interspeech.2017-1048
@inproceedings{bosch17_interspeech,
author={L. ten Bosch and L. Boves and M. Ernestus},
title={{The Recognition of Compounds: A Computational Account}},
year=2017,
booktitle={Proc. Interspeech 2017},
pages={1158--1162},
doi={10.21437/Interspeech.2017-1048}
}