Search Results for author:
Found 37 papers, 15 papers with code
Linguistic Evaluation for the 2021 State-of-the-art Machine Translation Systems for German to English and English to German
We are using a semi-automated test suite in order to provide a fine-grained linguistic evaluation for state-of-the-art machine translation systems.
Towards Personality-Aware Chatbots
Chatbots are increasingly used to automate operational processes in customer service.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective
In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content.
A Linguistically Motivated Test Suite to Semi-Automatically Evaluate German–English Machine Translation Output
Furthermore, we present various exemplary applications of our test suite that have been implemented in the past years, like contributions to the Conference of Machine Translation, the usage of the test suite and MT outputs for quality estimation, and the expansion of the test suite to the language pair Portuguese–English.
Subjective Text Complexity Assessment for German
In order to provide suitable text for the target audience, it is necessary to measure its complexity.
Overview of the GermEval 2022 Shared Task on Text Complexity Assessment of German Text
We designed the task as text regression in which participants developed models to predict complexity of pieces of text for a German learner in a range from 1 to 7.
Simulating Turn-Taking in Conversations with Delayed Transmission
We show how the turn-taking mechanisms modeled for conversations without delay perform in scenarios with delay and identify to which extend the simulation is able to model the delayed turn-taking observed in human conversation.
Claim extraction from text using transfer learning.
Building an end to end fake news detection system consists of detecting claims in text and later verifying them for their authenticity.
Best Practices for Crowd-based Evaluation of German Summarization: Comparing Crowd, Expert and Automatic Evaluation
On the one hand, the human assessment of summarization quality conducted by linguistic experts is slow, expensive, and still not a standardized procedure.
Reliability of Human Evaluation for Text Summarization: Lessons Learned and Challenges Ahead
Based on our empirical analysis, we provide guidelines to ensure the reliability of expert and non-expert evaluations, and we determine the factors that might affect the reliability of the human evaluation.
Using Neural Machine Translation Methods for Sign Language Translation
We examine methods and techniques, proven to be helpful for the text-to-text translation of spoken languages in the context of gloss-to-text translation systems, where the glosses are the written representation of the signs.
Perceptual Quality Dimensions of Machine-Generated Text with a Focus on Machine Translation
The quality of machine-generated text is a complex construct consisting of various aspects and dimensions.
Towards Hybrid Human-Machine Workflow for Natural Language Generation
In recent years, crowdsourcing has gained much attention from researchers to generate data for the Natural Language Generation (NLG) tools or to evaluate them.
Constructing Natural Language Explanations via Saliency Map Verbalization
Saliency maps can explain a neural model's prediction by identifying important input features.
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient's Perspective
In this work, we present the first corpus for German Adverse Drug Reaction (ADR) detection in patient-generated content.
A Transfer Learning Based Model for Text Readability Assessment in German
Text readability assessment has a wide range of applications for different target people, from language learners to people with disabilities.
A Medical Information Extraction Workbench to Process German Clinical Text
However, in the context of clinical text processing the number of accessible datasets is scarce -- and so is the number of existing tools.
Mediators: Conversational Agents Explaining NLP Model Behavior
The human-centric explainable artificial intelligence (HCXAI) community has raised the need for framing the explanation process as a conversation between human and machine.
When Performance is not Enough -- A Multidisciplinary View on Clinical Decision Support
Scientific publications about machine learning in healthcare are often about implementing novel methods and boosting the performance - at least from a computer science perspective.
MuLVE, A Multi-Language Vocabulary Evaluation Data Set
Vocabulary learning is vital to foreign language learning.
A Feature Extraction based Model for Hate Speech Identification
This paper presents TU Berlin team experiments and results on the task 1A and 1B of the shared task on hate speech and offensive content identification in Indo-European languages 2021.
Thermostat: A Large Collection of NLP Model Explanations and Analysis Tools
To facilitate research, we present Thermostat which consists of a large collection of model explanations and accompanying analysis tools.
Towards Human-Free Automatic Quality Evaluation of German Summarization
Evaluating large summarization corpora using humans has proven to be expensive from both the organizational and the financial perspective.
Full-Reference Speech Quality Estimation with Attentional Siamese Neural Networks
In this paper, we present a full-reference speech quality prediction model with a deep learning approach.
Deep Learning Based Assessment of Synthetic Speech Naturalness
Further, we show that the reliability of deep learning-based naturalness prediction can be improved by transfer learning from speech quality prediction models that are trained on objective POLQA scores.
Bias-Aware Loss for Training Image and Speech Quality Prediction Models from Multiple Datasets
The ground truth used for training image, video, or speech quality prediction models is based on the Mean Opinion Scores (MOS) obtained from subjective experiments.
NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasets
In this paper, we present an update to the NISQA speech quality prediction model that is focused on distortions that occur in communication networks.
Efficient Explanations from Empirical Explainers
Amid a discussion about Green AI in which we see explainability neglected, we explore the possibility to efficiently approximate computationally expensive explainers.
Incorporating Wireless Communication Parameters into the E-Model Algorithm
However, the NB, WB, and FB E-model algorithms do not consider wireless techniques used in these networks, such as Multiple-Input-Multiple-Output (MIMO) systems, which are used to improve the communication system robustness in the presence of different types of wireless channel degradation.
Fine-grained linguistic evaluation for state-of-the-art Machine Translation
This paper describes a test suite submission providing detailed statistics of linguistic performance for the state-of-the-art German-English systems of the Fifth Conference of Machine Translation (WMT20).
Evaluating German Transformer Language Models with Syntactic Agreement Tests
Most of the studies were conducted for the English language, however.
From Witch's Shot to Music Making Bones -- Resources for Medical Laymen to Technical Language and Vice Versa
This also applies to information about a person's health status.
Towards Deep Learning Methods for Quality Assessment of Computer-Generated Imagery
Video gaming streaming services are growing rapidly due to new services such as passive video streaming, e. g. Twitch. tv, and cloud gaming, e. g. Nvidia Geforce Now.
Impact of the Number of Votes on the Reliability and Validity of Subjective Speech Quality Assessment in the Crowdsourcing Approach
The subjective quality of transmitted speech is traditionally assessed in a controlled laboratory environment according to ITU-T Rec.
Multimedia
Untrue.News: A New Search Engine For Fake Stories
In this paper, we demonstrate Untrue News, a new search engine for fake stories.
Subjective Assessment of Text Complexity: A Dataset for German Language
This paper presents TextComplexityDE, a dataset consisting of 1000 sentences in German language taken from 23 Wikipedia articles in 3 different article-genres to be used for developing text-complexity predictor models and automatic text simplification in German language.
Train, Sort, Explain: Learning to Diagnose Translation Models
Evaluating translation models is a trade-off between effort and detail.
