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16 papers · 1 filter
Sentiment-Aware Measure (SAM) for Evaluating Sentiment Transfer by Machine Translation Systems
Hadeel Saadany, Constantin Orasan, Emad Mohamed +1
In translating text where sentiment is the main message, human translators give particular attention to sentiment-carrying words. The reason is that an incorrect translation of suc…
Self-Attentive Constituency Parsing for UCCA-based Semantic Parsing
Necva Bölücü, Burcu Can
Semantic parsing provides a way to extract the semantic structure of a text that could be understood by machines. It is utilized in various NLP applications that require text compr…
BLEU, METEOR, BERTScore: Evaluation of Metrics Performance in Assessing Critical Translation Errors in Sentiment-oriented Text
Hadeel Saadany, Constantin Orasan
Social media companies as well as authorities make extensive use of artificial intelligence (AI) tools to monitor postings of hate speech, celebrations of violence or profanity. Si…
Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation
Diptesh Kanojia, Marina Fomicheva, Tharindu Ranasinghe +3
Current Machine Translation (MT) systems achieve very good results on a growing variety of language pairs and datasets. However, they are known to produce fluent translation output…
FBERT: A Neural Transformer for Identifying Offensive Content
Diptanu Sarkar, Marcos Zampieri, Tharindu Ranasinghe +1
Transformer-based models such as BERT, XLNET, and XLM-R have achieved state-of-the-art performance across various NLP tasks including the identification of offensive language and h…
Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathi
Saurabh Gaikwad, Tharindu Ranasinghe, Marcos Zampieri +1
The widespread presence of offensive language on social media motivated the development of systems capable of recognizing such content automatically. Apart from a few notable excep…