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For many reasons, Mennonite Low German is a language whose documentation and investigation is of great importance for linguistics. To date, most research projects that deal with this language and/ or its speakers have had a relatively narrow focus, with many of the data cited being of limited relevance beyond the projects for which they were collected. In order to create a resource for a broad range of researchers, especially those working on Mennonite Low German, the dataset presented here has been transformed into a structured and searchable corpus that is accessible online. The translations of 46 English, Spanish, or Portuguese stimulus sentences into Mennonite Low German by 321 consultants form the core of the MEND-corpus (Mennonite Low German in North and South America) in the Archive for Spoken German. In addition to describing the origin of this corpus and discussing possibilities and limitations for further research, we discuss the technical structure and search possibilities of the Database for Spoken German. Among other things, this database allows for a structured search of metadata, a context-sensitive token search, and the generation of virtual corpora that can be shared with others. Moreover, thanks to its text-sound alignment, one can easily switch from a particular text section of the corpus to the corresponding audio section. Aside from the desire to equip the reader with the technical knowledge necessary to use this corpus, a further goal of this paper is to demonstrate that the corpus still offers many possibilities for future research.
This paper examines multi-unit turns that allow speakers to retrospectively close the prior sequence while prospectively launching a new sequence, which Schegloff (1986) referred to as interlocking organization. Using English telephone conversations as data, we focus on how multi-unit turns are used for topic shifts, and show that interlocking organization operates in conjunction with other phonetic and lexical features, such as increased pitch and overt markers of disjunction (e.g., “listen”). In addition, speakers utilize an audible inbreath that is placed between the first and the second units as a central interactional resource to project further talk, thereby suppressing speaker transition and possibly highlighting the action delivered in the second unit as being distinctly new. We propose that interlocking multi-unit turns, when used to make topically disjunctive moves, promote progressivity by avoiding a possible lapse in turn transition
Smooth turn-taking in conversation depends in part on speakers being able to communicate their intention to hold or cede the floor. Both prosodic and gestural cues have been shown to be used in this context. We investigate the interplay of pitch movements and hand gestures at locations at which speaker change becomes relevant, comparing their use in German and Swedish. We find that there are some shared functions of prosody and gesture with regard to turn-taking in the two languages, but that these shared functions appear to be mediated by the different phonological demands on pitch in the two languages.
Looking at gestures as a means for communication, they can serve conversational participants at several levels. As co-speech gestures, they can add information to the verbally expressed content and they can serve to manage turn-taking. In order to look closer at the interplay between these resources in face-to face conversation, we annotated hand gestures, syntactic completion points and the related turn-organisation, and measured the timing of gesture strokes and their lexical/phrasal referent. In a case study on German, we observe the trend that speakers vary less in gesturelexis on- and offsets when keeping the turn after syntactic completions than at speaker changes, backchannel or other locations of a conversation. This indicates that timing properties of non-verbal cues interact with verbal cues to manage turn-taking.
A syntax-based scheme for the annotation and segmentation of German spoken language interactions
(2018)
Unlike corpora of written language where segmentation can mainly be derived from orthographic punctuation marks, the basis for segmenting spoken language corpora is not predetermined by the primary data, but rather has to be established by the corpus compilers. This impedes consistent querying and visualization of such data. Several ways of segmenting have been proposed,
some of which are based on syntax. In this study, we developed and evaluated annotation and segmentation guidelines in reference to the topological field model for German. We can show that these guidelines are used consistently across annotators. We also investigated the influence of various interactional settings with a rather simple measure, the word-count per segment and unit-type. We observed that the word count and the distribution of each unit type differ in varying interactional settings and that our developed segmentation and annotation guidelines are used consistently across annotators. In conclusion, our syntax-based segmentations reflect interactional properties that are intrinsic to the social interactions that participants are involved in. This can be used for further analysis of social interaction and opens the possibility for automatic segmentation of transcripts.
There have been several attempts to annotate communicative functions to utterances of verbal feedback in English previously. Here, we suggest an annotation scheme for verbal and non-verbal feedback utterances in French including the categories base, attitude, previous and visual. The data comprises conversations, maptasks and negotiations from which we extracted ca. 13,000 candidate feedback utterances and gestures. 12 students were recruited for the annotation campaign of ca. 9,500 instances. Each instance was annotated by between 2 and 7 raters. The evaluation of the annotation agreement resulted in an average best-pair kappa of 0.6. While the base category with the values acknowledgement, evaluation, answer, elicit and other achieves good agreement, this is not the case for the other main categories. The data sets, which also include automatic extractions of lexical, positional and acoustic features, are freely available and will further be used for machine learning classification experiments to analyse the form-function relationship of feedback.
Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of all linguistic theories that take social interaction involving language into account. However, determining communicative functions is a notoriously difficult task both for human interpreters and systems. It involves an interpretative process that integrates various sources of information. Existing work on communicative function classification comes from either dialogue act tagging where it is generally coarse grained concerning the feed- back phenomena or it is token-based and does not address the variety of forms that feed- back utterances can take. This paper introduces an annotation framework, the dataset and the related annotation campaign (involving 7 raters to annotate nearly 6000 utterances). We present its evaluation not merely in terms of inter-rater agreement but also in terms of usability of the resulting reference dataset both from a linguistic research perspective and from a more applicative viewpoint.
Feedback utterances are among the most frequent in dialogue. Feedback is also a crucial aspect of linguistic theories that take social interaction, involving language, into account. This paper introduces the corpora and datasets of a project scrutinizing this kind of feedback utterances in French. We present the genesis of the corpora (for a total of about 16 hours of transcribed and phone force-aligned speech) involved in the project. We introduce the resulting datasets and discuss how they are being used in on-going work with focus on the form-function relationship of conversational feedback. All the corpora created and the datasets produced in the framework of this project will be made available for research purposes.
In order to explore the influence of context on the phonetic design of talk-in-interaction, we investigated the pitch characteristics of short turns (insertions) that are produced by one speaker between turns from another speaker. We investigated the hypothesis that the speaker of the insertion designs her turn as a pitch match to the prior turn in order to align with the previous speaker’s agenda, whereas non-matching displays that the speaker of the insertion is non-aligning, for example to initiate a new action. Data were taken from the AMI meeting corpus, focusing on the spontaneous talk of first-language English participants. Using sequential analysis, 177 insertions were classified as either aligning or non-aligning in accordance with definitions of these terms in the Conversation Analysis literature. The degree of similarity between the pitch contour of the insertion and that of the prior speaker’s turn was measured, using a new technique that integrates normalized F0 and intensity information. The results showed that aligning insertions were significantly more similar to the immediately preceding turn, in terms of pitch contour, than were non-aligning insertions. This supports the view that choice of pitch contour is managed locally, rather than by reference to an intonational lexicon.