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Using the Google Ngram Corpora for six different languages (including two varieties of English), a large-scale time series analysis is conducted. It is demonstrated that diachronic changes of the parameters of the Zipf–Mandelbrot law (and the parameter of the Zipf law, all estimated by maximum likelihood) can be used to quantify and visualize important aspects of linguistic change (as represented in the Google Ngram Corpora). The analysis also reveals that there are important cross-linguistic differences. It is argued that the Zipf–Mandelbrot parameters can be used as a first indicator of diachronic linguistic change, but more thorough analyses should make use of the full spectrum of different lexical, syntactical and stylometric measures to fully understand the factors that actually drive those changes.
This paper presents an extension to the Stuttgart-Tübingen TagSet, the standard part-of-speech tag set for German, for the annotation of spoken language. The additional tags deal with hesitations, backchannel signals, interruptions, onomatopoeia and uninterpretable material. They allow one to capture phenomena specific to spoken language while, at the same time, preserving inter-operability with already existing corpora of written language.
Von Grammatikern erwartet man Auskunft darüber, wie man zu reden und zu schreiben hat, eine Erwartung, die sich auf die Annahme stutzt, es stehe grundsätzlich immer schon fest, was in Sprachen wie etwa dem Deutschen als korrekt gelten kann. Tatsächlich kann jedoch nicht einmal davon ausgegangen werden, dass es so etwas wie das Deutsche als eindeutig bestimmten Gegenstand gibt. Alles, was als Deutsch zu fassen ist, sind ungezählte schriftliche und - sofern aufgezeichnet - mündliche Äußerungen. Bis vor wenigen Jahren waren diese Daten praktisch nur unzureichend zu nutzen, weshalb Grammatikern wenig anderes übrig blieb, als auf der schmalen Basis durch Introspektion gewonnener Daten Simulationen eines allgemeinen Sprachgebrauchs zu entwickeln. Mit der Verfügung über riesige Korpora maschinenlesbarer Texte haben sich die Voraussetzungen für die Untersuchung grammatischer Strukturen entscheidend verändert. Für die Grammatikforschung ergaben sich damit neue Perspektiven: zum einen ein radikaler Bruch mit der Tradition grammatischer Analysen, der weitgehend auf eine statistische Auswertung von Kookkurrenzen setzt, zum andern - weniger radikal, mehr traditionsverbunden - die Möglichkeit, konventionell kompetenzgestutzt erarbeitete Regelhypothesen anhand von Daten zu validieren, wie sie in sehr großen Textkorpora vorliegen und dem, was als Deutsch gelten kann, so nah kommen, wie dies irgend erreichbar ist, da sie durchweg in dem Bemühen zustande kamen, sich korrekt auszudrucken.
In the NLP literature, adapting a parser to new text with properties different from the training data is commonly referred to as domain adaptation. In practice, however, the differences between texts from different sources often reflect a mixture of domain and genre properties, and it is by no means clear what impact each of those has on statistical parsing. In this paper, we investigate how differences between articles in a newspaper corpus relate to the concepts of genre and domain and how they influence parsing performance of a transition-based dependency parser. We do this by applying various similarity measures for data point selection and testing their adequacy for creating genre-aware parsing models.
Linguistic query systems are special purpose IR applications. We present a novel state-of-the-art approach for the efficient exploitation of very large linguistic corpora, combining the advantages of relational database management systems (RDBMS) with the functional MapReduce programming model. Our implementation uses the German DEREKO reference corpus with multi-layer
linguistic annotations and several types of text-specific metadata, but the proposed strategy is language-independent and adaptable to large-scale multilingual corpora.
We present the annotation of information structure in the MULI project. To learn more about the information structuring means in prosody, syntax and discourse, theory- independent features were defined for each level. We describe the features and illustrate them on an example sentence. To investigate the interplay of features, the representation has to allow for inspecting all three layers at the same time. This is realised by a stand-off XML mark-up with the word as the basic unit. The theory-neutral XML stand-off annotation allows integrating this resource with other linguistic resources such as the Tiger Treebank for German or the Penn treebank for English.
While written corpora can be exploited without any linguistic annotations, speech corpora need at least a basic transcription to be of any use for linguistic research. The basic annotation of speech data usually consists of time-aligned orthographic transcriptions. To answer phonetic or phonological research questions, phonetic transcriptions are needed as well. However, manual annotation is very time-consuming and requires considerable skill and near-native competence. Therefore it can take years of speech corpus compilation and annotation before any analyses can be carried out. In this paper, approaches that address the transcription bottleneck of speech corpus exploitation are presented and discussed, including crowdsourcing the orthographic transcription, automatic phonetic alignment, and query-driven annotation. Currently, query-driven annotation and automatic phonetic alignment are being combined and applied in two speech research projects at the Institut für Deutsche Sprache (IDS), whereas crowdsourcing the orthographic transcription still awaits implementation.