Search Results for author: Elke Teich

Found 17 papers, 0 papers with code

EPIC UdS - Creation and Applications of a Simultaneous Interpreting Corpus

no code implementations LREC 2022 Heike Przybyl, Ekaterina Lapshinova-Koltunski, Katrin Menzel, Stefan Fischer, Elke Teich

In this paper, we describe the creation and annotation of EPIC UdS, a multilingual corpus of simultaneous interpreting for English, German and Spanish.

Exploring diachronic syntactic shifts with dependency length: the case of scientific English

no code implementations UDW (COLING) 2020 Tom S Juzek, Marie-Pauline Krielke, Elke Teich

Our starting assumption is that over time, Scientific English develops specific syntactic choice preferences that increase efficiency in (expert-to-expert) communication.

How Human is Machine Translationese? Comparing Human and Machine Translations of Text and Speech

no code implementations WS 2020 Yuri Bizzoni, Tom S Juzek, Cristina Espa{\~n}a-Bonet, Koel Dutta Chowdhury, Josef van Genabith, Elke Teich

Some translationese features tend to appear in simultaneous interpreting with higher frequency than in human text translation, but the reasons for this are unclear.

Machine Translation Translation

The Royal Society Corpus 6.0: Providing 300+ Years of Scientific Writing for Humanistic Study

no code implementations LREC 2020 Stefan Fischer, J{\"o}rg Knappen, Katrin Menzel, Elke Teich

We present a new, extended version of the Royal Society Corpus (RSC), a diachronic corpus of scientific English now covering 300+ years of scientific writing (1665--1996).

Grammar and Meaning: Analysing the Topology of Diachronic Word Embeddings

no code implementations WS 2019 Yuri Bizzoni, Stefania Degaetano-Ortlieb, Katrin Menzel, Pauline Krielke, Elke Teich

The paper showcases the application of word embeddings to change in language use in the domain of science, focusing on the Late Modern English period (17-19th century).

Clustering Diachronic Word Embeddings +1

Using relative entropy for detection and analysis of periods of diachronic linguistic change

no code implementations COLING 2018 Stefania Degaetano-Ortlieb, Elke Teich

We present a data-driven approach to detect periods of linguistic change and the lexical and grammatical features contributing to change.

Modeling intra-textual variation with entropy and surprisal: topical vs. stylistic patterns

no code implementations WS 2017 Stefania Degaetano-Ortlieb, Elke Teich

We present a data-driven approach to investigate intra-textual variation by combining entropy and surprisal.

Modeling Diachronic Change in Scientific Writing with Information Density

no code implementations COLING 2016 Raphael Rubino, Stefania Degaetano-Ortlieb, Elke Teich, Josef van Genabith

In this paper we investigate the introduction of information theory inspired features to study long term diachronic change on three levels: lexis, part-of-speech and syntax.

General Classification Informativeness

The Royal Society Corpus: From Uncharted Data to Corpus

no code implementations LREC 2016 Hannah Kermes, Stefania Degaetano-Ortlieb, Ashraf Khamis, J{\"o}rg Knappen, Elke Teich

We present the Royal Society Corpus (RSC) built from the Philosophical Transactions and Proceedings of the Royal Society of London.

Sentence

Data Mining with Shallow vs. Linguistic Features to Study Diversification of Scientific Registers

no code implementations LREC 2014 Stefania Degaetano-Ortlieb, Peter Fankhauser, Hannah Kermes, Ekaterina Lapshinova-Koltunski, Noam Ordan, Elke Teich

We present a methodology to analyze the linguistic evolution of scientific registers with data mining techniques, comparing the insights gained from shallow vs. linguistic features.

Text Categorization

Exploring and Visualizing Variation in Language Resources

no code implementations LREC 2014 Peter Fankhauser, J{\"o}rg Knappen, Elke Teich

Language resources are often compiled for the purpose of variational analysis, such as studying differences between genres, registers, and disciplines, regional and diachronic variation, influence of gender, cultural context, etc.

Feature Discovery for Diachronic Register Analysis: a Semi-Automatic Approach

no code implementations LREC 2012 Stefania Degaetano-Ortlieb, Ekaterina Lapshinova-Koltunski, Elke Teich

In this paper, we present corpus-based procedures to semi-automatically discover features relevant for the study of recent language change in scientific registers.

Text Classification

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