Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2017 Sep 26:8:1648.
doi: 10.3389/fpsyg.2017.01648. eCollection 2017.

Word Order and Voice Influence the Timing of Verb Planning in German Sentence Production

Affiliations

Word Order and Voice Influence the Timing of Verb Planning in German Sentence Production

Sebastian Sauppe. Front Psychol. .

Abstract

Theories of incremental sentence production make different assumptions about when speakers encode information about described events and when verbs are selected, accordingly. An eye tracking experiment on German testing the predictions from linear and hierarchical incrementality about the timing of event encoding and verb planning is reported. In the experiment, participants described depictions of two-participant events with sentences that differed in voice and word order. Verb-medial active sentences and actives and passives with sentence-final verbs were compared. Linear incrementality predicts that sentences with verbs placed early differ from verb-final sentences because verbs are assumed to only be planned shortly before they are articulated. By contrast, hierarchical incrementality assumes that speakers start planning with relational encoding of the event. A weak version of hierarchical incrementality assumes that only the action is encoded at the outset of formulation and selection of lexical verbs only occurs shortly before they are articulated, leading to the prediction of different fixation patterns for verb-medial and verb-final sentences. A strong version of hierarchical incrementality predicts no differences between verb-medial and verb-final sentences because it assumes that verbs are always lexically selected early in the formulation process. Based on growth curve analyses of fixations to agent and patient characters in the described pictures, and the influence of character humanness and the lack of an influence of the visual salience of characters on speakers' choice of active or passive voice, the current results suggest that while verb planning does not necessarily occur early during formulation, speakers of German always create an event representation early.

Keywords: German; eye tracking; incremental sentence production; passive; verb planning; word order.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Example stimulus picture.
Figure 2
Figure 2
Proportions of active sentences as a function of agent (A) and patient (P) humanness. Bars indicate 95% confidence intervals (Agresti and Coull, 1998).
Figure 3
Figure 3
Densities and box plots of speech onset latencies (relative to stimulus picture onset) for three German sentence types; width of the violins is proportional to the number of underlying data points (Hintze and Nelson, 1998).
Figure 4
Figure 4
Proportions of fixations to agents and patients during the production of three German sentence types. Proportions are based on fixations to agent and patient AOIs and to “whitespace” (Holmqvist et al., 2011) not covered by these AOIs. Ribbons indicate 95% multinomial confidence intervals (Sison and Glaz, ; Villacorta, 2012); vertical lines indicate analysis time windows.

References

    1. Agresti A. (2007). An Introduction to Categorical Data Analysis, 2nd Edn. Hoboken, NJ: John Wiley and Sons; 10.1002/0470114754 - DOI
    1. Agresti A., Coull B. A. (1998). Approximate is better than “exact” for interval estimation of binomial proportions. Amer. Stat. 52, 119–126.
    1. Allum P. H., Wheeldon L. R. (2007). Planning scope in spoken sentence production: the role of grammatical units. J. Exp. Psychol. 33, 791–810. 10.1037/0278-7393.33.4.791 - DOI - PubMed
    1. Barr D. J. (2008). Analyzing ‘visual world’ eyetracking data using multilevel logistic regression. J. Mem. Lang. 59, 457–474. 10.1016/j.jml.2007.09.002 - DOI
    1. Barr D. J. (2013). Random effects structure for testing interactions in linear mixed-effects models. Front. Psychol. 4:328. 10.3389/fpsyg.2013.00328 - DOI - PMC - PubMed

LinkOut - more resources