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Found 30 papers, 5 papers with code
Annotating Near-Identity from Coreference Disagreements
We present an extension of the coreference annotation in the English NP4E and the Catalan AnCora-CA corpora with near-identity relations, which are borderline cases of coreference.
CLCM - A Linguistic Resource for Effective Simplification of Instructions in the Crisis Management Domain and its Evaluations
This article presents a new linguistic resource in the form of Controlled Language (CL) guidelines for manual text simplification in the CM domain which aims to address high TC in the CM domain and produce clear messages to be used in crisis situations.
What Makes You Stressed? Finding Reasons From Tweets
Detecting stress from social media gives a non-intrusive and inexpensive alternative to traditional tools such as questionnaires or physiological sensors for monitoring mental state of individuals.
Enhancing Unsupervised Sentence Similarity Methods with Deep Contextualised Word Representations
Calculating Semantic Textual Similarity (STS) plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction.
Contextualised Word Representations
Information Retrieval
+6
Toponym Detection in the Bio-Medical Domain: A Hybrid Approach with Deep Learning
This paper compares how different machine learning classifiers can be used together with simple string matching and named entity recognition to detect locations in texts.
Semantic Textual Similarity with Siamese Neural Networks
Calculating the Semantic Textual Similarity (STS) is an important research area in natural language processing which plays a significant role in many applications such as question answering, document summarisation, information retrieval and information extraction.
Sentence Simplification for Semantic Role Labelling and Information Extraction
The paper begins with our observation of challenges in the intrinsic evaluation of sentence simplification systems, which motivates the use of extrinsic evaluation of these systems with respect to other NLP tasks.
A Survey of the Perceived Text Adaptation Needs of Adults with Autism
NLP approaches to automatic text adaptation often rely on user-need guidelines which are generic and do not account for the differences between various types of target groups.
TransQuest at WMT2020: Sentence-Level Direct Assessment
This paper presents the team TransQuest's participation in Sentence-Level Direct Assessment shared task in WMT 2020.
RGCL at SemEval-2020 Task 6: Neural Approaches to Definition Extraction
This paper presents the RGCL team submission to SemEval 2020 Task 6: DeftEval, subtasks 1 and 2.
Is it Great or Terrible? Preserving Sentiment in Neural Machine Translation of Arabic Reviews
We address this problem by fine-tuning an NMT model with respect to sentiment polarity showing that this approach can significantly help with correcting sentiment errors detected in the online translation of Arabic UGC.
TransQuest: Translation Quality Estimation with Cross-lingual Transformers
Recent years have seen big advances in the field of sentence-level quality estimation (QE), largely as a result of using neural-based architectures.
Fake or Real? A Study of Arabic Satirical Fake News
One very common type of fake news is satire which comes in a form of a news website or an online platform that parodies reputable real news agencies to create a sarcastic version of reality.
RGCL at SemEval-2020 Task 6: Neural Approaches to DefinitionExtraction
This paper presents the RGCL team submission to SemEval 2020 Task 6: DeftEval, subtasks 1 and 2.
An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers
Most studies on word-level Quality Estimation (QE) of machine translation focus on language-specific models.
Challenges in Translation of Emotions in Multilingual User-Generated Content: Twitter as a Case Study
In this research, we assess whether automatic translation tools can be a successful real-life utility in transferring emotion in user-generated multilingual data such as tweets.
BLEU, METEOR, BERTScore: Evaluation of Metrics Performance in Assessing Critical Translation Errors in Sentiment-oriented Text
The adequacy of the whole process relies on the assumption that the evaluation metrics used give a reliable indication of the quality of the translation.
Sentiment-Aware Measure (SAM) for Evaluating Sentiment Transfer by Machine Translation Systems
In translating text where sentiment is the main message, human translators give particular attention to sentiment-carrying words.
Biographical: A Semi-Supervised Relation Extraction Dataset
The dataset, which is aimed towards digital humanities (DH) and historical research, is automatically compiled by aligning sentences from Wikipedia articles with matching structured data from sources including Pantheon and Wikidata.
A Semi-supervised Approach for a Better Translation of Sentiment in Dialectical Arabic UGT
In the online world, Machine Translation (MT) systems are extensively used to translate User-Generated Text (UGT) such as reviews, tweets, and social media posts, where the main message is often the author's positive or negative attitude towards the topic of the text.
Evaluation of Chinese-English Machine Translation of Emotion-Loaded Microblog Texts: A Human Annotated Dataset for the Quality Assessment of Emotion Translation
In this paper, we focus on how current Machine Translation (MT) tools perform on the translation of emotion-loaded texts by evaluating outputs from Google Translate according to a framework proposed in this paper.
SurreyAI 2023 Submission for the Quality Estimation Shared Task
Quality Estimation (QE) systems are important in situations where it is necessary to assess the quality of translations, but there is no reference available.
Google Translate Error Analysis for Mental Healthcare Information: Evaluating Accuracy, Comprehensibility, and Implications for Multilingual Healthcare Communication
This study explores the use of Google Translate (GT) for translating mental healthcare (MHealth) information and evaluates its accuracy, comprehensibility, and implications for multilingual healthcare communication through analysing GT output in the MHealth domain from English to Persian, Arabic, Turkish, Romanian, and Spanish.
A Semi-Automated Live Interlingual Communication Workflow Featuring Intralingual Respeaking: Evaluation and Benchmarking
In this paper, we present a semi-automated workflow for live interlingual speech-to-text communication which seeks to reduce the shortcomings of existing ASR systems: a human respeaker works with a speaker-dependent speech recognition software (e. g., Dragon Naturally Speaking) to deliver punctuated same-language output of superior quality than obtained using out-of-the-box automatic speech recognition of the original speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
SURREY-CTS-NLP at WASSA2022: An Experiment of Discourse and Sentiment Analysis for the Prediction of Empathy, Distress and Emotion
This paper summarises the submissions our team, SURREY-CTS-NLP has made for the WASSA 2022 Shared Task for the prediction of empathy, distress and emotion.
