Search Results for author:
Found 11 papers, 3 papers with code
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.
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.
Better Transcription of UK Supreme Court Hearings
Transcription of legal proceedings is very important to enable access to justice.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
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.
PLOD: An Abbreviation Detection Dataset for Scientific Documents
This paper presents PLOD, a large-scale dataset for abbreviation detection and extraction that contains 160k+ segments automatically annotated with abbreviations and their long forms.
Ranked #1 on
AbbreviationDetection
on PLOD-unfiltered
An Ensemble Approach to Acronym Extraction using Transformers
Acronyms are abbreviated units of a phrase constructed by using initial components of the phrase in a text.
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.
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.
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.
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.
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.
