Search Results for author: Arne Köhn

Found 9 papers, 5 papers with code

MC-Saar-Instruct: a Platform for Minecraft Instruction Giving Agents

no code implementations SIGDIAL (ACL) 2020 Arne Köhn, Julia Wichlacz, Christine Schäfer, Álvaro Torralba, Joerg Hoffmann, Alexander Koller

We present a comprehensive platform to run human-computer experiments where an agent instructs a human in Minecraft, a 3D blocksworld environment.

Aligning Actions Across Recipe Graphs

1 code implementation EMNLP 2021 Lucia Donatelli, Theresa Schmidt, Debanjali Biswas, Arne Köhn, Fangzhou Zhai, Alexander Koller

Recipe texts are an idiosyncratic form of instructional language that pose unique challenges for automatic understanding.


Generating Instructions at Different Levels of Abstraction

no code implementations COLING 2020 Arne Köhn, Julia Wichlacz, Álvaro Torralba, Daniel Höller, Jörg Hoffmann, Alexander Koller

When generating technical instructions, it is often convenient to describe complex objects in the world at different levels of abstraction.


Every child should have parents: a taxonomy refinement algorithm based on hyperbolic term embeddings

1 code implementation ACL 2019 Rami Aly, Shantanu Acharya, Alexander Ossa, Arne Köhn, Chris Biemann, Alexander Panchenko

We introduce the use of Poincar\'e embeddings to improve existing state-of-the-art approaches to domain-specific taxonomy induction from text as a signal for both relocating wrong hyponym terms within a (pre-induced) taxonomy as well as for attaching disconnected terms in a taxonomy.

Finding the way from ä to a: Sub-character morphological inflection for the SIGMORPHON 2018 Shared Task

1 code implementation15 Sep 2018 Fynn Schröder, Marcel Kamlot, Gregor Billing, Arne Köhn

In this paper we describe the system submitted by UHH to the CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection.

Morphological Inflection

Open Source Automatic Speech Recognition for German

2 code implementations26 Jul 2018 Benjamin Milde, Arne Köhn

The models are trained on a total of 412 hours of German read speech data and we achieve a relative word error reduction of 26% by adding data from the Spoken Wikipedia Corpus to the previously best freely available German acoustic model recipe and dataset.

Ranked #6 on Speech Recognition on TUDA (using extra training data)

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

An Empirical Analysis of the Correlation of Syntax and Prosody

no code implementations15 Jun 2018 Arne Köhn, Timo Baumann, Oskar Dörfler

The relation of syntax and prosody (the syntax--prosody interface) has been an active area of research, mostly in linguistics and typically studied under controlled conditions.

Incremental Natural Language Processing: Challenges, Strategies, and Evaluation

no code implementations31 May 2018 Arne Köhn

Incrementality is ubiquitous in human-human interaction and beneficial for human-computer interaction.

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