David Schlangen

发表

Investigating Fluidity for Human-Robot Interaction with Real-time, Real-world Grounding Strategies

Julian Hough, David Schlangen, J. Hough, 2016, SIGDIAL Conference.

Timing and Grounding in Motor Skill Coaching Interaction: Consequences for the Information State

S. Kopp, J. Hough, David Schlangen, 2015 .

The InproTK 2012 release

David Schlangen, Timo Baumann, David Schlangen, 2012, SDCTD@NAACL-HLT.

Modelling Sub-Utterance Phenomena in Spoken Dialogue Systems

David Schlangen, Okko Buß, David Schlangen, 2010 .

Towards Deep End-of-Turn Prediction for Situated Spoken Dialogue Systems

Julian Hough, David Schlangen, Angelika Maier, 2017, INTERSPEECH.

Unifying Self- and Other-Repair

David Schlangen, R. Fernández, J. Ginzburg, 2007 .

Dialogue Structure of Coaching Sessions

S. Kopp, J. Hough, David Schlangen, 2014 .

Learning to Describe Multimodally from Parallel Unimodal Data ? A Pilot Study on Verbal and Sketched Object Descriptions

Kazunori Komatani, David Schlangen, Sina Zarrieß, 2018 .

Resolving Fragments using Discourse Information

A. Lascarides, David Schlangen, 2002 .

Resolving Underspecification using Discourse Information

David Schlangen, Alex Lascarides, Ann Copestake, 2001 .

CETP: An Automated Theorem Prover for a Fragment of Common Sense Entailment

David Schlangen, Alex Lascarides, A. Lascarides, 2002 .

The Potsdam Dialogue Corpora: Transcription and Annotation Manual

David Schlangen, Raquel Fernández, David Schlangen, 2008 .

Semantics and Dialogue

David Schlangen, 2015 .

Information-Seeking Chat : Dialogue Management by Topic Structure

David Schlangen, Manfred Stede, 2004 .

Collaborating on Utterances with a Spoken Dialogue System Using an ISU-based Approach to Incremental Dialogue Management

David Schlangen, Timo Baumann, Okko Buß, 2010, SIGDIAL Conference.

Practices in Dialogue

David Schlangen, 2010 .

Norm Participation Grounds Language

David Schlangen, 2022, ArXiv.

Generating Coherent and Informative Descriptions for Groups of Visual Objects and Categories: A Simple Decoding Approach

H. Wersing, David Schlangen, Nazia Attari, 2022 .

Anaphoric Phenomena in Situated dialog: A First Round of Annotations

David Schlangen, Simon Dobnik, S. Loáiciga, 2022, CRAC.

Norm Participation Grounds Language

David Schlangen, 2022, CLASP.

DUEL: A Multi-lingual Multimodal Dialogue Corpus for Disfluency, Exclamations and Laughter

Ye Tian, Jonathan Ginzburg, Julian Hough, 2016, LREC.

A cross-linguistic study on turn-taking and temporal alignment in verbal interaction

David Schlangen, Spyros Kousidis, Stavros Skopeteas, 2013, INTERSPEECH.

TELIDA: A Package for Manipulation and Visualization of Timed Linguistic Data

David Schlangen, Timo Baumann, Titus Malsburg, 2009, SIGDIAL Conference.

Push-to-talk ain't always bad! Comparing Different Interactivity Settings in Task-oriented Dialogue

David Schlangen, Raquel Fernández, Tatjana Lucht, 2007 .

Speaking through a noisy channel - experiments on inducing clarification behaviour in human-human dialogue

David Schlangen, Raquel Fernández, David Schlangen, 2007, INTERSPEECH.

Beyond Repair – Testing the Limits of the Conversational Repair System

David Schlangen, Raquel Fernández, David Schlangen, 2007, SIGDIAL.

Referring under Restricted Interactivity Conditions

Raquel Fernández, David Schlangen, Tatjana Lucht, 2007, SIGDIAL.

INTERACTION IN TASK-ORIENTED HUMAN-HUMAN DIALOGUE: THE EFFECTS OF DIFFERENT TURN-TAKING POLICIES

David Schlangen, Raquel Fernández, Kepa Joseba Rodríguez, 2006, 2006 IEEE Spoken Language Technology Workshop.

From reaction to prediction: experiments with computational models of turn-taking

David Schlangen, David Schlangen, 2006, INTERSPEECH.

Are you talking to me?: Improving the Robustness of Dialogue Systems in a Multi Party HRI Scenario by Incorporating Gaze Direction and Lip Movement of Attendees

Sven Wachsmuth, Franz Kummert, David Schlangen, 2016, HAI.

Towards a Types-As-Classifiers Approach to Dialogue Processing in Human-Robot Interaction

Julian Hough, David Schlangen, Lorenzo Jamone, 2018 .

Evaluating Prosodic Processing for Incremental Speech Synthesis

David Schlangen, Timo Baumann, David Schlangen, 2012, INTERSPEECH.

Targeting the Benchmark: On Methodology in Current Natural Language Processing Research pdf

David Schlangen, David Schlangen, 2020, ACL.

Towards Finding and Fixing Fragments—Using ML to Identify Non-Sentential Utterances and their Antecedents in Multi-Party Dialogue

David Schlangen, David Schlangen, 2005, ACL.

The Power of a Glance: Evaluating Embodiment and Turn-Tracking Strategies of an Active Robotic Overhearer

David Schlangen, Spyros Kousidis, David Schlangen, 2015, AAAI Spring Symposia.

What we can learn from Dialogue Systems that don't work: On Dialogue Systems as Cognitive Models

David Schlangen, David Schlangen, 2009 .

Decoding Strategies for Neural Referring Expression Generation

David Schlangen, Sina Zarrieß, David Schlangen, 2018, INLG.

An Overview of Natural Language State Representation for Reinforcement Learning pdf

David Schlangen, Brielen Madureira, David Schlangen, 2020, ArXiv.

The slurk Interaction Server Framework: Better Data for Better Dialog Models

David Schlangen, Tim Diekmann, Jana Gotze, 2022, LREC.

Is Incoherence Surprising? Targeted Evaluation of Coherence Prediction from Language Models

David Schlangen, Anne Beyer, Sharid Lo'aiciga, 2021, NAACL.

A Multimodal In-Car Dialogue System That Tracks The Driver's Attention

Stefan Kopp, Hendrik Buschmeier, David Schlangen, 2014, ICMI.

Real-Time Understanding of Complex Discriminative Scene Descriptions

David DeVault, David Schlangen, Ramesh R. Manuvinakurike, 2016, SIGDIAL Conference.

MeetUp! A Corpus of Joint Activity Dialogues in a Visual Environment pdf

David Schlangen, Nikolai Ilinykh, Sina Zarriess, 2019, ArXiv.

Know What You Don’t Know: Modeling a Pragmatic Speaker that Refers to Objects of Unknown Categories

David Schlangen, Sina Zarrieß, David Schlangen, 2019, ACL.

Refer-iTTS: A System for Referring in Spoken Installments to Objects in Real-World Images

David Schlangen, Sina Zarrieß, Soledad López Gambino, 2017, INLG.

Easy Things First: Installments Improve Referring Expression Generation for Objects in Photographs

David Schlangen, Sina Zarrieß, David Schlangen, 2016, ACL.

Incrementally Tracking Reference in Human/Human Dialogue Using Linguistic and Extra-Linguistic Information

Takenobu Tokunaga, David Schlangen, Ryu Iida, 2015, NAACL.

Reciprocal Learning via Dialogue Interaction: Challenges and Prospects

Staffan Larsson, Robin Cooper, Jonathan Ginzburg, 2011, IJCAI 2011.

Introduction to the Special Issue on Incremental Processing in Dialogue

David Schlangen, Hannes Rieser, David Schlangen, 2011 .

Towards Reducing and Managing Uncertainty in Spoken Dialogue Systems

David Schlangen, Andrea Corradini, Raquel Fernández, 2007 .

Markov Logic Networks for Situated Incremental Natural Language Understanding

David Schlangen, Casey Redd Kennington, David Schlangen, 2012, SIGDIAL Conference.

Building and Applying Perceptually-Grounded Representations of Multimodal Scene Descriptions

David Schlangen, Ting Han, Casey Kennington, 2015 .

Incremental Semantics for Dialogue Processing: Requirements, and a Comparison of Two Approaches

Jonathan Ginzburg, Julian Hough, David Schlangen, 2015, IWCS.

Incremental Construction of Robust but Deep Semantic Representations for Use in Responsive Dialogue Systems

David Schlangen, Andreas Peldszus, David Schlangen, 2012, Coling 2012.

The INPROTK 2012 Release: A Toolkit for Incremental Spoken Dialogue Processing

David Schlangen, Timo Baumann, David Schlangen, 2012, ITG Conference on Speech Communication.

Joint Satisfaction of Syntactic and Pragmatic Constraints Improves Incremental Spoken Language Understanding

David Schlangen, Andreas Peldszus, Timo Baumann, 2012, EACL.

Comparing Local and Sequential Models for Statistical Incremental Natural Language Understanding

David Schlangen, Timo Baumann, Silvan Heintze, 2010, SIGDIAL Conference.

Beyond Single-Mindedness: A Figure-Ground Reversal for the Cognitive Sciences

L. Suchman, E. Hutchins, Riccardo Fusaroli, 2023, Cogn. Sci..

Dialogue Games for Benchmarking Language Understanding: Motivation, Taxonomy, Strategy

David Schlangen, 2023, ArXiv.

What A Situated Language-Using Agent Must be Able to Do: A Top-Down Analysis

David Schlangen, 2023, ArXiv.

PentoRef: A Corpus of Spoken References in Task-oriented Dialogues

David DeVault, Julian Hough, David Schlangen, 2016, LREC.

Instruction Clarification Requests in Multimodal Collaborative Dialogue Games: Tasks, and an Analysis of the CoDraw Dataset

David Schlangen, Brielen Madureira, 2023, Conference of the European Chapter of the Association for Computational Linguistics.

It's Not What You Do, It's How You Do It: Grounding Uncertainty for a Simple Robot

Julian Hough, David Schlangen, J. Hough, 2017, 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI.

Can Visual Dialogue Models Do Scorekeeping? Exploring How Dialogue Representations Incrementally Encode Shared Knowledge

David Schlangen, Brielen Madureira, 2022, ACL.

From Explainability to Explanation: Using a Dialogue Setting to Elicit Annotations with Justifications

Martin Heckmann, David Schlangen, Nazia Attari, 2019, SIGdial.

Grounded Agreement Games: Emphasizing Conversational Grounding in Visual Dialogue Settings pdf

David Schlangen, David Schlangen, 2019, ArXiv.

Language Tasks and Language Games: On Methodology in Current Natural Language Processing Research pdf

David Schlangen, David Schlangen, 2019, ArXiv.

Interpreting Situated Dialogue Utterances: an Update Model that Uses Speech, Gaze, and Gesture Information

David Schlangen, Spyros Kousidis, Casey Redd Kennington, 2013, SIGDIAL Conference.

Evaluating a minimally invasive laboratory architecture for recording multimodal conversational data

Petra Wagner, Zofia Malisz, David Schlangen, 2012, Interspeech 2012.

A General, Abstract Model of Incremental Dialogue Processing

Gabriel Skantze, David Schlangen, Gabriel Skantze, 2009, EACL.

A Simple Method for Resolution of Definite Reference in a Shared Visual Context

David Schlangen, Alexander Siebert, David Schlangen, 2008, SIGDIAL Workshop.

Space Efficient Context Encoding for Non-Task-Oriented Dialogue Generation with Graph Attention Transformer

David Schlangen, Jens Lehmann, Fabian Galetzka, 2021, ACL.

Form, Intonation and Function of Clarification Requests in German Task-Oriented Spoken Dialogues

Kepa Joseba Rodríguez, David Schlangen, K. Rodríguez, 2004 .

Causes and Strategies for Requesting Clarification in Dialogue

David Schlangen, David Schlangen, 2004, SIGDIAL Workshop.

Images in Language Space: Exploring the Suitability of Large Language Models for Vision & Language Tasks

David Schlangen, Sherzod Hakimov, Sherzod Hakimov, 2023, ACL.

New or Old? Exploring How Pre-Trained Language Models Represent Discourse Entities

David Schlangen, S. Loáiciga, Anne Beyer, 2022, COLING.

No sooner said than done? testing incrementality of semantic interpretations of spontaneous speech

David Schlangen, Timo Baumann, Michaela Atterer, 2009, INTERSPEECH.

The interpretation of non-sentential utterances in dialogue

David Schlangen, Alex Lascarides, A. Lascarides, 2003, SIGDIAL Workshop.

Disfluencies as intra-utterance dialogue moves

Jonathan Ginzburg, David Schlangen, Raquel Fernández, 2014 .

Self-repairs in German children ’ s peer interaction – initial explorations

David Schlangen, R. Fernández, J. Ginzburg, 2017 .

Joint, Incremental Disfluency Detection and Utterance Segmentation from Speech

Julian Hough, David Schlangen, J. Hough, 2017, EACL.

Natural Language Informs the Interpretation of Iconic Gestures: A Computational Approach

Julian Hough, David Schlangen, Ting Han, 2017, IJCNLP.

INPRO_iSS: A Component for Just-In-Time Incremental Speech Synthesis

David Schlangen, Timo Baumann, David Schlangen, 2012, ACL.

A compositional and constraint-based approach to non-sentential utterances

David Schlangen, Alex Lascarides, A. Lascarides, 2003 .

The Disfluency, Exclamation and Laughter in Dialogue (DUEL) Project

Jonathan Ginzburg, Julian Hough, David Schlangen, 2014 .

A Corpus of Controlled Opinionated and Knowledgeable Movie Discussions for Training Neural Conversation Models

David Schlangen, Fabian Galetzka, Chukwuemeka U. Eneh, 2020, LREC.

Towards Incremental Transformers: An Empirical Analysis of Transformer Models for Incremental NLU pdf

David Schlangen, Brielen Madureira, Patrick Kahardipraja, 2021, EMNLP.

Simple Learning and Compositional Application of Perceptually Grounded Word Meanings for Incremental Reference Resolution

David Schlangen, Casey Redd Kennington, David Schlangen, 2015, ACL.

Being data-driven is not enough: Revisiting interactive instruction giving as a challenge for NLG

David Schlangen, Sina Zarrieß, David Schlangen, 2018, HRI 2018.

The Task Matters: Comparing Image Captioning and Task-Based Dialogical Image Description

David Schlangen, Sina Zarrieß, Nikolai Ilinykh, 2018, INLG.

From “Before” to “After”: Generating Natural Language Instructions from Image Pairs in a Simple Visual Domain

Sina Zarrieß, Jana Götze, Henrik Voigt, 2020, INLG.

Visual Dialogue Needs Symmetry , Goals , and Dynamics : The Example of the MeetUp Task

David Schlangen, N. Ilinykh, Sina Zarrieß, 2018 .

clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents

David Schlangen, Sherzod Hakimov, Brielen Madureira, 2023, ArXiv.

Toward incremental dialogue act segmentation in fast-paced interactive dialogue systems

David DeVault, David Schlangen, Ramesh R. Manuvinakurike, 2016, SIGDIAL Conference.

Modelling dialogue: Challenges and Aproaches

David Schlangen, David Schlangen, 2005, Künstliche Intell..

Beyond Single-Mindedness: A Figure-Ground Reversal for the Cognitive Sciences

L. Suchman, E. Hutchins, Riccardo Fusaroli, 2023, Cogn. Sci..

Resolving References to Objects in Photographs using the Words-As-Classifiers Model pdf

David Schlangen, Sina Zarrieß, Casey Redd Kennington, 2015, ACL.

Yes, this Way! Learning to Ground Referring Expressions into Actions with Intra-episodic Feedback from Supportive Teachers

David Schlangen, Sherzod Hakimov, P. Sadler, 2023, ACL.

Generating Landmark-based Manipulation Instructions from Image Pairs

David Schlangen, Sina Zarrieß, Henrik Voigt, 2022, International Conference on Natural Language Generation.

Towards Generating Colour Terms for Referents in Photographs: Prefer the Expected or the Unexpected?

David Schlangen, Sina Zarrieß, David Schlangen, 2016, INLG.

A Discriminative Model for Perceptually-Grounded Incremental Reference Resolution

David Schlangen, Casey Redd Kennington, Livia Dia, 2015, IWCS.

Grounding, Justification, Adaptation: Towards Machines That Mean What They Say

David Schlangen, David Schlangen, 2016 .

Real-world Reference Game using the Words-as-Classifiers Model of Reference Resolution

David Schlangen, Casey Kennington, Maria Soledad Lopez Gambino, 2015 .

Neural Conversation Models and How to Rein Them in: A Survey of Failures and Fixes

David Schlangen, Anne Beyer, Fabian Galetzka, 2023, ArXiv.

The Road to Quality is Paved with Good Revisions: A Detailed Evaluation Methodology for Revision Policies in Incremental Sequence Labelling

David Schlangen, Brielen Madureira, Patrick Kahardipraja, 2023, SIGDIAL.

TAPIR: Learning Adaptive Revision for Incremental Natural Language Understanding with a Two-Pass Model

David Schlangen, Brielen Madureira, Patrick Kahardipraja, 2023, ACL.

Incremental Processing in the Age of Non-Incremental Encoders: An Empirical Assessment of Bidirectional Models for Incremental NLU pdf

David Schlangen, Brielen Madureira, David Schlangen, 2020, EMNLP.

Evaluation and Optimisation of Incremental Processors

David Schlangen, Timo Baumann, Okko Buß, 2011, Dialogue Discourse.

Incremental Reference Resolution: The Task, Metrics for Evaluation, and a Bayesian Filtering Model that is Sensitive to Disfluencies

David Schlangen, Timo Baumann, Michaela Atterer, 2009, SIGDIAL Conference.

Assessing and Improving the Performance of Speech Recognition for Incremental Systems

David Schlangen, Timo Baumann, Michaela Atterer, 2009, NAACL.

Recurrent neural networks for incremental disfluency detection

Julian Hough, David Schlangen, J. Hough, 2015, INTERSPEECH.

Natural Language Semantics With Pictures: Some Language & Vision Datasets and Potential Uses for Computational Semantics

David Schlangen, David Schlangen, 2019, IWCS.

Tell Me More: A Dataset of Visual Scene Description Sequences

Sina Zarrieß, David Schlangen, Nikolai Ilinykh, 2019, INLG.

A Corpus of Natural Multimodal Spatial Scene Descriptions

David Schlangen, Ting Han, David Schlangen, 2018, LREC.

Grounding Imperatives to Actions is Not Enough: A Challenge for Grounded NLU for Robots from Human-Human Data

Julian Hough, David Schlangen, Sina Zarriess, 2017 .

Grounding Language by Continuous Observation of Instruction Following

David Schlangen, Ting Han, David Schlangen, 2017, EACL.

Towards Incremental End-of-Utterance Detection in Dialogue Systems

David Schlangen, Timo Baumann, Michaela Atterer, 2008, COLING.

A General, Abstract Model of Incremental Dialogue Processing

Gabriel Skantze, David Schlangen, 2009, EACL.

Incremental Dialogue Processing in a Micro-Domain

Gabriel Skantze, David Schlangen, Gabriel Skantze, 2009, EACL.

A simple generative model of incremental reference resolution for situated dialogue

David Schlangen, Casey Redd Kennington, David Schlangen, 2017, Comput. Speech Lang..

On the Semantics and Pragmatics of Dysfluency

Jonathan Ginzburg, David Schlangen, Raquel Fernández, 2011, Amsterdam Colloquium on Logic, Language and Meaning.

Deictic gestures in coaching interactions

Stefan Kopp, Iwan de Kok, Julian Hough, 2016, MA3HMI@ICMI.

Draw and Tell: Multimodal Descriptions Outperform Verbal- or Sketch-Only Descriptions in an Image Retrieval Task

David Schlangen, Ting Han, David Schlangen, 2017, IJCNLP.

Discourse Structure and Information Structure: Interfaces and Prosodic Realization

David Schlangen, Ekaterina Jasinskaja, David Schlangen, 2004 .

Better Driving and Recall When In-car Information Presentation Uses Situationally-Aware Incremental Speech Output Generation

Stefan Kopp, Hendrik Buschmeier, David Schlangen, 2014, AutomotiveUI.

Situationally Aware In-Car Information Presentation Using Incremental Speech Generation: Safer, and More Effective

Stefan Kopp, Hendrik Buschmeier, David Schlangen, 2014, DM@EACL.

Silence, Please!: Interrupting In-Car Phone Conversations

David Schlangen, Casey Redd Kennington, Soledad López Gambino, 2017 .

! : Interrupting In-Car Phone Conversations

Soledad López Gambino, David Schlangen, C. Kennington, 2017 .

InproTK in Action: Open-Source Software for Building German-Speaking Incremental Spoken Dialogue Systems

David Schlangen, Timo Baumann, Okko Buß, 2010, ESSV.

Recognising Conversational Speech: What an Incremental ASR Should Do for a Dialogue System and How to Get There

Julian Hough, David Schlangen, Timo Baumann, 2016, IWSDS.

Reading Times Predict the Quality of Generated Text Above and Beyond Human Ratings

David Schlangen, Sina Zarrieß, Sebastian Loth, 2015, ENLG.

clembench: Using Game Play to Evaluate Chat-Optimized Language Models as Conversational Agents

David Schlangen, Sherzod Hakimov, Brielen Madureira, 2023, EMNLP.