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Found 40 papers, 8 papers with code
The CACAPO Dataset: A Multilingual, Multi-Domain Dataset for Neural Pipeline and End-to-End Data-to-Text Generation
This paper describes the CACAPO dataset, built for training both neural pipeline and end-to-end data-to-text language generation systems.
Gradations of Error Severity in Automatic Image Descriptions
Because our manipulated descriptions form minimal pairs with the reference descriptions, we are able to assess the impact of different kinds of errors on the perceived quality of the descriptions.
Evaluation rules! On the use of grammars and rule-based systems for NLG evaluation
NLG researchers often use uncontrolled corpora to train and evaluate their systems, using textual similarity metrics, such as BLEU.
Evaluating Task-oriented Dialogue Systems: A Systematic Review of Measures, Constructs and their Operationalisations
This review gives an extensive overview of evaluation methods for task-oriented dialogue systems, paying special attention to practical applications of dialogue systems, for example for customer service.
Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP
We report our efforts in identifying a set of previous human evaluations in NLP that would be suitable for a coordinated study examining what makes human evaluations in NLP more/less reproducible.
Neural Data-to-Text Generation Based on Small Datasets: Comparing the Added Value of Two Semi-Supervised Learning Approaches on Top of a Large Language Model
In terms of output quality, extending the training set of a data-to-text system with a language model using the pseudo-labeling approach did increase text quality scores, but the data augmentation approach yielded similar scores to the system without training set extension.
Preregistering NLP Research
Preregistration refers to the practice of specifying what you are going to do, and what you expect to find in your study, before carrying out the study.
Surface Realization Shared Task 2019 (MSR19): The Team 6 Approach
This study describes the approach developed by the Tilburg University team to the shallow track of the Multilingual Surface Realization Shared Task 2019 (SR{'}19) (Mille et al., 2019).
Automatic identification of writers' intentions: Comparing different methods for predicting relationship goals in online dating profile texts
Results show that LIWC and machine learning models correlate with human evaluations in terms of content-related labels.
A Personalized Data-to-Text Support Tool for Cancer Patients
In this paper, we present a novel data-to-text system for cancer patients, providing information on quality of life implications after treatment, which can be embedded in the context of shared decision making.
Best practices for the human evaluation of automatically generated text
Currently, there is little agreement as to how Natural Language Generation (NLG) systems should be evaluated.
On task effects in NLG corpus elicitation: a replication study using mixed effects modeling
Task effects in NLG corpus elicitation recently started to receive more attention, but are usually not modeled statistically.
Question Similarity in Community Question Answering: A Systematic Exploration of Preprocessing Methods and Models
Community Question Answering forums are popular among Internet users, and a basic problem they encounter is trying to find out if their question has already been posed before.
Neural data-to-text generation: A comparison between pipeline and end-to-end architectures
In contrast, recent neural models for data-to-text generation have been proposed as end-to-end approaches, where the non-linguistic input is rendered in natural language with much less explicit intermediate representations in-between.
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Automated learning of templates for data-to-text generation: comparing rule-based, statistical and neural methods
The current study investigated novel techniques and methods for trainable approaches to data-to-text generation.
Context-sensitive Natural Language Generation for robot-assisted second language tutoring
The L2TOR ITS is developed for the purpose of investigating the efficacy of robot-assisted second language tutoring in early childhood.
Enriching the WebNLG corpus
This paper describes the enrichment of WebNLG corpus (Gardent et al., 2017a, b), with the aim to further extend its usefulness as a resource for evaluating common NLG tasks, including Discourse Ordering, Lexicalization and Referring Expression Generation.
Making effective use of healthcare data using data-to-text technology
Financial reports are produced to assess healthcare organizations on some key performance indicators to steer their healthcare delivery.
Aspect-based summarization of pros and cons in unstructured product reviews
In the second evaluation, the gold-standard pros and cons were assessed along with the system output.
DIDEC: The Dutch Image Description and Eye-tracking Corpus
We present a corpus of spoken Dutch image descriptions, paired with two sets of eye-tracking data: Free viewing, where participants look at images without any particular purpose, and Description viewing, where we track eye movements while participants produce spoken descriptions of the images they are viewing.
Evaluating the text quality, human likeness and tailoring component of PASS: A Dutch data-to-text system for soccer
We present an evaluation of PASS, a data-to-text system that generates Dutch soccer reports from match statistics which are automatically tailored towards fans of one club or the other.
Varying image description tasks: spoken versus written descriptions
Automatic image description systems are commonly trained and evaluated on written image descriptions.
Surface Realization Shared Task 2018 (SR18): The Tilburg University Approach
This study describes the approach developed by the Tilburg University team to the shallow task of the Multilingual Surface Realization Shared Task 2018 (SR18).
NeuralREG: An end-to-end approach to referring expression generation
Traditionally, Referring Expression Generation (REG) models first decide on the form and then on the content of references to discourse entities in text, typically relying on features such as salience and grammatical function.
Linguistic realisation as machine translation: Comparing different MT models for AMR-to-text generation
In this paper, we study AMR-to-text generation, framing it as a translation task and comparing two different MT approaches (Phrase-based and Neural MT).
PASS: A Dutch data-to-text system for soccer, targeted towards specific audiences
We present PASS, a data-to-text system that generates Dutch soccer reports from match statistics.
Generating flexible proper name references in text: Data, models and evaluation
The model relies on the REGnames corpus, a dataset with 53, 102 proper name references to 1, 000 people in different discourse contexts.
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation
This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input.
