1 code implementation • SIGUL (LREC) 2022 • Pranaydeep Singh, Orphee De Clercq, Els Lefever
This paper reports on experiments for cross-lingual transfer using the anchor-based approach of Schuster et al. (2019) for English and a low-resourced language, namely Hindi.
no code implementations • CONSTRAINT (ACL) 2022 • Pranaydeep Singh, Aaron Maladry, Els Lefever
This paper describes the system we developed for the shared task ‘Hero, Villain and Victim: Dissecting harmful memes for Semantic role labelling of entities’ organised in the framework of the Second Workshop on Combating Online Hostile Posts in Regional Languages during Emergency Situation (Constraint 2022).
1 code implementation • EMNLP (LaTeCHCLfL, CLFL, LaTeCH) 2021 • Pranaydeep Singh, Gorik Rutten, Els Lefever
This paper presents a pilot study to automatic linguistic preprocessing of Ancient and Byzantine Greek, and morphological analysis more specifically.
no code implementations • WASSA (ACL) 2022 • Ellen De Geyndt, Orphee De Clercq, Cynthia Van Hee, Els Lefever, Pranaydeep Singh, Olivier Parent, Veronique Hoste
In this paper, we present the SentEMO platform, a tool that provides aspect-based sentiment analysis and emotion detection of unstructured text data such as reviews, emails and customer care conversations.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+1
no code implementations • COLING 2022 • Pranaydeep Singh, Els Lefever
In this research, we present pilot experiments to distil monolingual models from a jointly trained model for 102 languages (mBERT).
no code implementations • SEMEVAL 2021 • Pranaydeep Singh, Els Lefever
Internet memes have become ubiquitous in social media networks today.
no code implementations • SEMEVAL 2020 • Pranaydeep Singh, Nina Bauwelinck, Els Lefever
Internet memes have become a very popular mode of expression on social media networks today.
no code implementations • 23 Nov 2020 • Natesh Reddy, Pranaydeep Singh, Muktabh Mayank Srivastava
When performing Polarity Detection for different words in a sentence, we need to look at the words around to understand the sentiment.
Ranked #13 on
Aspect-Based Sentiment Analysis (ABSA)
on SemEval-2014 Task-4
(Restaurant (Acc) metric)
no code implementations • SEMEVAL 2020 • Pranaydeep Singh, Els Lefever
The second approach incorporates pre-trained English embeddings that are incrementally retrained with a set of Hinglish tweets.
no code implementations • LREC 2020 • Pranaydeep Singh, Els Lefever
We specifically investigate the use of these embeddings for a sentiment analysis task for Hinglish Tweets, viz.
no code implementations • LREC 2020 • Els Lefever, Sofie Labat, Pranaydeep Singh
This paper investigates the validity of combining more traditional orthographic information with cross-lingual word embeddings to identify cognate pairs in English-Dutch and French-Dutch.
no code implementations • 22 Aug 2018 • Pranaydeep Singh, Srikrishna Varadarajan, Ankit Narayan Singh, Muktabh Mayank Srivastava
We try to address the problem of document layout understanding using a simple algorithm which generalizes across multiple domains while training on just few examples per domain.