SFB 1102:  Information Density and Linguistic Encoding

• Subject Area: Humanities ; Computer Science, Systems and Electrical Engineering ; Social and Behavioural Sciences
• Term: since 2014
• Website: Homepage
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 232722074

Language provides not only the expressiveness needed to communicate, but also offers speakers a multitude of choices regarding how they may encode their messages – from the choice of words, structuring of syntactic elements, and arranging sentences in discourse. The overarching aim of the CRC is to investigate the extent to which linguistic encoding decisions are driven by the goal of speakers to modulate the distribution, and density, of information across the linguistic signal. Against the background of information theory (Shannon), language is viewed from the perspective of (bounded) rational communication, according to which interlocutors strive to optimize the encoding of their utterances to (i) successfully convey their intended message, and (ii) optimize their cognitive effort. While there is a long tradition of trying to understand language systems and their use in terms of complexity, the definition of this notion is often imprecise and specific to particular linguistic levels. More recently, however, converging evidence indicates that the ease of processing linguistic material is correlated with its contextually determined predictability, which can be formally expressed as information density, or “surprisal”. Surprisal has been shown to be a strong predictor of linguistic encoding choices across linguistic levels, from the phonetic and grammatical to the semantic and discourse levels and across languages. Importantly, recent evidence has revealed that information density is not uniquely determined by linguistic context, but develops dynamically within specific situations, across interactions and over longer periods of time, with interlocutors continuously adapting to each other and the environment. The CRC investigates how surprisal, situation and task combine to drive the dynamics of language use, both in real-time interactions as well as from a broader temporal perspective, considering effects ranging from fast learning to long-term memory, as well as variety formation and language change within specific languages and across languages.

• DFG Programme: Collaborative Research Centres

Current projects

• A01 - Neurobehavioural Correlates of Surprisal in Online Comprehension (Project Heads Brouwer, Ph.D., Harm ;  Crocker, Matthew W. )
• A05 - The Role of Language Experience and Surprisal for Learning and Memory (Project Heads Häuser, Katja ;  Kray, Jutta ;  Mani, Nivedita ;  Staudte, Maria )
• A06 - Expectancy-based mechanisms during language comprehension and their relation to memory formation and retrieval (Project Heads Bader, Regine ;  Mecklinger, Axel )
• A07 - Controlling Information Density in Discourse Generation (Project Heads Hoffmann, Jörg ;  Koller, Alexander )
• A08 - Adapting Text Generation to Individual Users (Project Heads Demberg, Vera ;  Koller, Alexander )
• B01 - Information Density in English Scientific Writing: A Diachronic Perspective (Project Heads Degaetano-Ortlieb, Ph.D., Stefania ;  Kermes, Hannah ;  Ordan, Noam ;  Teich, Elke )
• B02 - Cognitive Modelling of Information Density for Discourse Relations (Project Heads Demberg, Vera ;  Scholman, Merel )
• B03 - Information Theory and Ellipsis Redundancy (Project Heads Drenhaus, Heiner ;  Lemke, Robin ;  Reich, Ingo )
• B04 - Modelling and Measuring Information Density (Project Head Klakow, Dietrich )
• B06 - Unravelling Linguistic Knowledge via Multilingual Embedding Spaces and Latent Information (Project Heads España i Bonet, Cristina ;  van Genabith, Josef ;  Rubino, Raphael )
• B07 - Translation as Rational Communication (Project Heads Lapshinova-Koltunski, Ekaterina ;  Teich, Elke )
• C01 - Information Density and the Predictability of Phonetic Structure (Project Heads Andreeva, Bistra ;  Möbius, Bernd )
• C03 - Rational Encoding and Decoding of Referring Expressions (Project Heads Crocker, Matthew W. ;  Drenhaus, Heiner ;  Reich, Ingo ;  Venhuizen, Ph.D., Noortje )
• C04 - Mutual Intelligibility and Surprisal in Slavic Intercomprehension (INCOMSLAV-3) (Project Heads Avgustinova, Tania ;  Klakow, Dietrich ;  Marti, Roland Walter ;  Möbius, Bernd )
• C06 - Information Management as a Factor for Syntactic Variation in the History of German (Project Heads Dipper, Stefanie ;  Speyer, Augustin )
• C07 - Cross-linguistic Information-Theoretic Modelling of Communicative Efficiency (Project Head Verkerk, Annemarie )
• MGK - Integrated Research Training Group (Project Heads Mecklinger, Axel ;  Möbius, Bernd ;  Reich, Ingo )
• T01 - Information Density and Linguistic Encoding in “Leichte Sprache” (IDeaLite) (Project Heads Reich, Ingo ;  Teich, Elke ;  Zinsmeister, Heike )
• Z - Central Tasks (Project Head Teich, Elke )

Completed projects

• A02 - Script Knowledge for Modelling Semantic Expectation (Project Heads Pinkal, Manfred ;  Thater, Stefan )
• A03 - Modelling the Information Density of Event Sequences in Texts (Project Heads Demberg, Vera ;  Koller, Alexander ;  Pinkal, Manfred ;  Thater, Stefan )
• A04 - Language Comprehension in a Noisy Channel (Project Heads Demberg, Vera ;  Klakow, Dietrich ;  Kray, Jutta )
• B05 - The Extraction of Complex Information and Encoding Density (EXCITED) (Project Head Uszkoreit, Hans )
• C05 - Information Density Aware Text-to-Speech Synthesis (Project Head Steiner, Ingmar )

• Applicant Institution: Universität des Saarlandes
• Participating University: Ruhr-Universität Bochum; Universität Hamburg
• Participating Institution: Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI); Forschungsgruppe Multilinguale Technologien (MLT)
• Spokesperson: Professorin Dr. Elke Teich