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Natural language Processing tools are mostly developed for and optimized on newspaper texts, and often Show a substantial performance drop when applied to other types of texts such as Twitter feeds, Chat data or Internet forum posts. We explore a range of easy-to-implement methods of adapting existing part-of-speech taggers to improve their performance on Internet texts. Our results show that these methods can improve tagger performance substantially.
This document presents ongoing work related to spoken language data within a project that aims to establish a common and unified infrastructure for the sustainable provision of linguistic primary research data at the Institut für Deutsche Sprache (IDS). In furtherance of its mission to “document the German language as it is currently used”, the project expects to enable the research community to access a broad empirical base of working material via a single platform. While the goal is to eventually cover all linguistically relevant digital resources of the IDS, including lexicographic information systems such as the IDS German Vocabulary Portal, OWID, written language corpora such as the IDS German Reference Corpus, DeReKo, and spoken language corpora such as the IDS German Speech Corpus for Research and Teaching, FOLK, the work presented here predominantly focuses on the latter type of data, i.e. speech corpora. Within this context, the present document pictures the project’s contributions to the development of standards and best practice guidelines concerning data storage, process documentation and legal issues for the sustainable preservation and long-term accessibility of primary linguistic research data.
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.