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Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus
(2021)
Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics. However, most of these large raw corpora are either available only for English or not available to the general public due to copyright issues. Nevertheless, there are some examples of freely available multilingual corpora for training Deep Learning NLP models, such as the OSCAR and Paracrawl corpora. However, they have quality issues, especially for low-resource languages. Moreover, recreating or updating these corpora is very complex. In this work, we try to reproduce and improve the goclassy pipeline used to create the OSCAR corpus. We propose a new pipeline that is faster, modular, parameterizable, and well documented. We use it to create a corpus similar to OSCAR but larger and based on recent data. Also, unlike OSCAR, the metadata information is at the document level. We release our pipeline under an open source license and publish the corpus under a research-only license.
Preface
(2019)
Preface
(2020)
This study investigates cross-language differences in pitch range and variation in four languages from two language groups: English and German (Germanic) and Bulgarian and Polish (Slavic). The analysis is based on large multi-speaker corpora (48 speakers for Polish, 60 for each of the other three languages). Linear mixed models were computed that include various distributional measures of pitch level, span and variation, revealing characteristic differences across languages and between language groups. A classification experiment based on the relevant parameter measures (span, kurtosis and skewness values for pitch distributions for each speaker) succeeded in separating the language groups.
This study presents the results of a large-scale comparison of various measures of pitch range and pitch variation in two Slavic (Bulgarian and Polish) and two Germanic (German and British English) languages. The productions of twenty-two speakers per language (eleven male and eleven female) in two different tasks (read passages and number sets) are compared. Significant differences between the language groups are found: German and English speakers use lower pitch maxima, narrower pitch span, and generally less variable pitch than Bulgarian and Polish speakers. These findings support the hypothesis that inguistic communities tend to be characterized by particular pitch profiles.
Based on specific linguistic landmarks in the speech signal, this study investigates pitch level and pitch span differences in English, German, Bulgarian and Polish. The analysis is based on 22 speakers per language (11 males and 11 females). Linear mixed models were computed that include various linguistic measures of pitch level and span, revealing characteristic differences across languages and between language groups. Pitch level appeared to have significantly higher values for the female speakers in the Slavic than the Germanic group. The male speakers showed slightly different results, with only the Polish speakers displaying significantly higher mean values for pitch level than the German males. Overall, the results show that the Slavic speakers tend to have a wider pitch span than the German speakers. But for the linguistic measure, namely for span between the initial peaks and the non-prominent valleys, we only find the difference between Polish and German speakers. We found a flatter intonation contour in German than in Polish, Bulgarian and English male and female speakers and differences in the frequency of the landmarks between languages. Concerning “speaker liveliness” we found that the speakers from the Slavic group are significantly livelier than the speakers from the Germanic group.
Prominence has been widely studied on the word level and the syllable level. An extensive study comparing the two approaches is missing in the literature. This study investigates how word and syllable prominence relate to each other in German. We find that perceptual ratings based on the word level are more extreme than those based on the syllable level. The correlations between word prominence and acoustic features are greater than the correlations between syllable prominence and acoustic features.
In our study we use the experimental framework of priming to manipulate our subjects’ expectations of syllable prominence in sentences with a well-defined syntactic and phonological structure. It shows that it is possible to prime prominence patterns and that priming leads to significant differences in the judgment of syllable prominence.
Streefkerk defines prominence as the perceptually outstanding parts in spoken language. An optimal rating scale for syllable prominence has not been found yet. This paper evaluates a 4-point, an 11-point, a 31-point, and a continuous scale for the rating of syllable prominence and gives support for scales using a higher number of levels. Priming effects found by Arnold, et al., could only be replicated using the 31-point scale.
The classification of verbs in Levin's (1993) English Verb Classes and Alternations: A preliminary Investigation, on the basis of both intuitive semantic grouping and their participation in valence alternations, is often used by the NLP community as evidence of the semantic similarity of verbs (Jing & McKeown 1998; Lapata & Brew 1999; Kohl et al. 1998). In this paper, we compare the Levin classification with the work of the FrameNet project (Fillmore & Baker 2001), where words (not just verbs) are grouped according to the conceptual structures (frames) that underlie them and their combinatorial patterns are inductively derived from corpus evidence. This means that verbs grouped together in FrameNet (FN) might be semantically similar but have different (or no) alternations, and that verbs which share the same alternation might be represented in two different semantic frames.
Der Beitrag befasst sich zunächst mit der Satzklammer des Deutschen aus der Perspektive der Informationsverteilung. Nachdem gezeigt ist, dass sie als Informationsklammer fungiert, wird ihre Interaktion mit den Teilen gespaltener Nominalphrasen untersucht. Dabei zeigen sich zwei interessante Befunde:
• die Satzklammer und die NP-Teile unterstützen sich bei der Informationsklammerbildung; insbesondere können die Spalt-NP-Teile Akzent tragen;
• die Spalt-NP-Teile können alleine die Rolle einer Informationsklammer spielen, wodurch eine Topikalisierung des Partizips II möglich wird.
As the Web ought to be considered as a series of sources rather than as a source in itself, a problem facing corpus construction resides in meta-information and categorization. In addition, we need focused data to shed light on particular subfields of the digital public sphere. Blogs are relevant to that end, especially if the resulting web texts can be extracted along with metadata and made available in coherent and clearly describable collections.
Wenn man verschiedenartige Forschungsdaten über Metadaten inhaltlich beschreiben möchte, sind bibliografische Angaben allein nicht ausreichend. Vielmehr benötigt man zusätzliche Beschreibungsmittel, die der Natur und Komplexität gegebener Forschungsressourcen Rechnung tragen. Verschiedene Arten von Forschungsdaten bedürfen verschiedener Metadatenprofile, die über gemeinsame Komponenten definiert werden. Solche Forschungsdaten können gesammelt (z.B. über OAI-PMH-Harvesting) und mittels Facetten-basierter Suche über eine einheitliche Schnittstelle exploriert werden. Der beschriebene Anwendungskontext kann über sprachwissenschaftliche Daten hinaus verallgemeinert werden.
Linguistics is facing the challenge of many other sciences as it continues to grow into increasingly complex subfields, each with its own separate or overarching branches. While linguists are certainly aware of the overall structure of the research field, they cannot follow all developments other than those of their subfields. It is thus important to help specialists but also newcomers alike to bushwhack through evolved or unknown territory of linguistic data. A considerable amount of research data in linguistics is described with metadata. While studies described and published in archived journals and conference proceedings receive a quite homogeneous set of metadata tags — e.g., author, title, publisher —, this does not hold for the empirical data and analyses that underlie such studies. Moreover, lexicons, grammars, experimental data, and other types of resources come in different forms; and to make things worse, their description in terms of metadata is also not uniform, if existing at all. These problems are well-known and there are now a number of international initiatives — e.g., CLARIN, FlareNet, MetaNet, DARIAH — to build infrastructures for managing linguistic resources. The NaLiDa project, funded by the German Research Foundation, aims at facilitating the management and access to linguistic resources originating from German research institutions. In cooperation with the German SFB 833 research center, we are developing a combination of faceted and full-text search to give integrated access through heterogeneous metadata sets. Our approach is supported by a central registry for metadata field descriptors, and a component repository for structured groups of data categories as larger building blocks.
In conversation, speakers need to plan and comprehend language in parallel in order to meet the tight timing constraints of turn taking. Given that language comprehension and speech production planning both require cognitive resources and engage overlapping neural circuits, these two tasks may interfere with one another in dialogue situations. Interference effects have been reported on a number of linguistic processing levels, including lexicosemantics. This paper reports a study on semantic processing efficiency during language comprehension in overlap with speech planning, where participants responded verbally to questions containing semantic illusions. Participants rejected a smaller proportion of the illusions when planning their response in overlap with the illusory word than when planning their response after the end of the question. The obtained results indicate that speech planning interferes with language comprehension in dialogue situations, leading to reduced semantic processing of the incoming turn. Potential explanatory processing accounts are discussed.
The goal of the MULI (MUltiLingual Information structure) project is to empirically analyse information structure in German and English newspaper texts. In contrast to other projects in which information structure is annotated and investigated (e.g. in the Prague Dependency Treebank, which mirrors the basic information about the topic-focus articulation of the sentence), we do not annotate theory-biased categories like topic-focus or theme-rheme. Trying to be as theory-independent as possible, we annotate those features which are relevant to information structure and on the basis of which typical patterns, co-occurrences or correlations can be determined. We distinguish between three annotation levels: syntax, discourse and prosody. The data is based on the TIGER Corpus for German and the Penn Treebank for English, since the existing information on part-of-speech and syntactic structure can be re-used for our purposes. The actual annotation of an English example sequence illustrates our choice of categories on each level. Their combination offers the possibility to investigate how information structure is realised and can be interpreted.
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.
We present an approach on how to investigate what kind of semantic information is regularly associated with the structural markup of scientific articles. This approach addresses the need for an explicit formal description of the semantics of text-oriented XML-documents. The domain of our investigation is a corpus of scientific articles from psychology and linguistics from both English and German online available journals. For our analyses, we provide XML-markup representing two kinds of semantic levels: the thematic level (i.e. topics in the text world that the article is about) and the functional or rhetorical level. Our hypothesis is that these semantic levels correlate with the articles’ document structure also represented in XML. Articles have been annotated with the appropriate information. Each of the three informational levels is modelled in a separate XML document, since in our domain, the different description levels might conflict so that it is impossible to model them within a single XML document. For comparing and mining the resulting multi-layered XML annotations of one article, a Prolog-based approach is used. It focusses on the comparison of XML markup that is distributed among different documents. Prolog predicates have been defined for inferring relations between levels of information that are modelled in separate XML documents. We demonstrate how the Prolog tool is applied in our corpus analyses.
The present article describes the first stage of the KorAP project, launched recently at the Institut für Deutsche Sprache (IDS) in Mannheim, Germany. The aim of this project is to develop an innovative corpus analysis platform to tackle the increasing demands of modern linguistic research. The platform will facilitate new linguistic findings by making it possible to manage and analyse primary data and annotations in the petabyte range, while at the same time allowing an undistorted view of the primary linguistic data, and thus fully satisfying the demands of a scientific tool. An additional important aim of the project is to make corpus data as openly accessible as possible in light of unavoidable legal restrictions, for instance through support for distributed virtual corpora, user-defined annotations and adaptable user interfaces, as well as interfaces and sandboxes for user-supplied analysis applications. We discuss our motivation for undertaking this endeavour and the challenges that face it. Next, we outline our software implementation plan and describe development to-date.
The paper presents best practices and results from projects in four countries dedicated to the creation of corpora of computer-mediated communication and social media interactions (CMC). Even though there are still many open issues related to building and annotating corpora of that type, there already exists a range of accessible solutions which have been tested in projects and which may serve as a starting point for a more precise discussion of how future standards for CMC corpora may (and should) be shaped like.