11 citations · 29 across the 21 of their papers we have counts for
6 papers · 1 filter
End-to-End Lip Reading in Romanian with Cross-Lingual Domain Adaptation and Lateral Inhibition
Emilian-Claudiu Mănescu, Răzvan-Alexandru Smădu, Andrei-Marius Avram +2
Lip reading or visual speech recognition has gained significant attention in recent years, particularly because of hardware development and innovations in computer vision. While co…
Towards Improving the Performance of Pre-Trained Speech Models for Low-Resource Languages Through Lateral Inhibition
Andrei-Marius Avram, Răzvan-Alexandru Smădu, Vasile Păiş +3
With the rise of bidirectional encoder representations from Transformer models in natural language processing, the speech community has adopted some of their development methodolog…
Multilingual Multiword Expression Identification Using Lateral Inhibition and Domain Adaptation
Andrei-Marius Avram, Verginica Barbu Mititelu, Vasile Păiş +2
Correctly identifying multiword expressions (MWEs) is an important task for most natural language processing systems since their misidentification can result in ambiguity and misun…
Adversarial Capsule Networks for Romanian Satire Detection and Sentiment Analysis
Sebastian-Vasile Echim, Răzvan-Alexandru Smădu, Andrei-Marius Avram +2
Satire detection and sentiment analysis are intensively explored natural language processing (NLP) tasks that study the identification of the satirical tone from texts and extracti…
RoBERTweet: A BERT Language Model for Romanian Tweets
Iulian-Marius Tăiatu, Andrei-Marius Avram, Dumitru-Clementin Cercel +1
Developing natural language processing (NLP) systems for social media analysis remains an important topic in artificial intelligence research. This article introduces RoBERTweet, t…
Romanian Multiword Expression Detection Using Multilingual Adversarial Training and Lateral Inhibition
Andrei-Marius Avram, Verginica Barbu Mititelu, Dumitru-Clementin Cercel
Multiword expressions are a key ingredient for developing large-scale and linguistically sound natural language processing technology. This paper describes our improvements in auto…