Verb clusters in colloquial German

Bader, Markus; Schmid, Tanja

doi:10.1007/s10828-009-9032-x

Cited by 47 publications

(20 citation statements)

References 30 publications

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“…Because auxiliary inversion in verb clusters is known to involve a large amount of dialectal variation (see Schmid & Vogel 2004), Bader & Schmid (2009) also looked at the regional background of their participants. Since the pattern of well-formedness just described was found to be independent of participants' regional background, Bader & Schmid (2009) concluded that the order 3-1-2 is an optional variant in Colloquial German although not in Standard German. The remaining four orders received rather low judgments but still showed certain gradations which will be discussed later.…”

Section: Subexperiments C : Verb-cluster Linearizationmentioning

confidence: 99%

Toward a model of grammaticality judgments

2009

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This paper presents three experiments that investigate the relationship between gradient and binary judgments of grammaticality. In the first two experiments, two different groups of participants judged sentences by the method of magnitude estimation and by the method of speeded grammaticality judgments in a single session. The two experiments involved identical sentence materials but they differed in the order in which the two procedures were applied. The results show a high correlation between the magnitude estimation data and the speeded grammaticality judgments data, both within a session and across the two sessions. The third experiment was a questionnaire study in which participants judged the same sentences as either grammatical or ungrammatical without time pressure. This experiment yielded results quite similar to those of the other two experiments. Thus gradient and binary judgments both provide valuable and reliable sources for linguistic theory when assessed in an experimentally controlled way. We present a model based on Signal Detection Theory which specifies how gradient grammaticality scores are mapped to binary grammaticality judgments. Finally, we compare our experimental results to existing corpus data in order to inquire into the relationship between grammaticality and frequency of usage.

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Section: Subexperiments C : Verb-cluster Linearizationmentioning

confidence: 99%

Toward a model of grammaticality judgments

2009

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“…Bader & Schmid (2009) show that speakers from all German speaking regions give the 312 order a high acceptability rating, though not as high as for the 132 order.…”

Section: Order Preferences In German 3-verb Clustersmentioning

confidence: 82%

10 Function words in rhythmic optimisation

Vogel¹,

Vijver²,

Kotz³

et al. 2015

Rhythm in Cognition and Grammar

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“…For German, the syntactic evidence for this distinction is particularly controversial and some accounts consider all these types of verbs as projecting VP structures (see Sternefeld 2006: 507ff.). In order to understand the behavior of verbal clusters, it is useful to conflate the different categories of verbs assuming that they create projections of the same type embedded in each other; see (9) (see previous analyses of verb clusters in this vein ;Haider 2003;Schmidt & Vogel 2004;Bader & Schmid 2009;Salzmann 2013 The frequencies of functional and lexical verbs in our dataset are reported in Table 5. Simple lexical verbs without any functional verb occur more frequently in non-public (68%) than in public texts (57.1%); see Table 7.…”

Section: Overview Of the Datamentioning

confidence: 99%

Self-embedding and complexity in oral registers

Verhoeven

Lehmann

2018

Glossa: A Journal of General Linguistics

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This article reports the results of a study on the self-embedding depth of nominal, verbal and clausal projections in spoken corpora of German. We compared two spoken registers featuring public and non-public (i.e. private) conversation by measuring the depth of self-embedding in C, V, and N projections. The findings confirm the hypothesis that the familiarity of the speech situation (public vs. non-public speech) has a significant impact on complexity in terms of self-embedding: speakers use more self-embedding in public speech production in different syntactic projections. In addition, we examined previous assumptions about the differences between right, left, and center embedding in C projections. The results confirm a preference against center embedding in non-public texts, which reflects the complexity of center embedding. Finally, we find evidence that the depth of self-embedding in V and C projections is correlated. This finding suggests that self-embedding depth is part of a general strategy, i.e., speakers select more or less complex structures (of different types) depending on factors of the speech situation.

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Verb clusters in colloquial German

Cited by 47 publications

References 30 publications

Toward a model of grammaticality judgments

Toward a model of grammaticality judgments

10 Function words in rhythmic optimisation

Self-embedding and complexity in oral registers

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