no code implementations • EAMT 2022 • Dimitra Anastasiou, Anders Ruge, Radu Ion, Svetlana Segărceanu, George Suciu, Olivier Pedretti, Patrick Gratz, Hoorieh Afkari
This paper is about a multilingual chatbot developed for public administration within the CEF funded project ENRICH4ALL.
1 code implementation • 29 Oct 2024 • Vasile Păiş, Radu Ion, Andrei-Marius Avram, Maria Mitrofan, Dan Tufiş
This paper presents the design and evolution of the RELATE platform.
no code implementations • 30 Jun 2023 • Andrei-Marius Avram, Răzvan-Alexandru Smădu, Vasile Păiş, Dumitru-Clementin Cercel, Radu Ion, Dan Tufiş
With the rise of bidirectional encoder representations from Transformer models in natural language processing, the speech community has adopted some of their development methodologies.
no code implementations • CLIB 2022 • Radu Ion, Andrei-Marius Avram, Vasile Păiş, Maria Mitrofan, Verginica Barbu Mititelu, Elena Irimia, Valentin Badea
The paper will present the QA system and its integration with the Romanian language technologies portal RELATE, the COVID-19 data set and different evaluations of the QA performance.
no code implementations • 22 Nov 2021 • Vasile Păiş, Radu Ion, Andrei-Marius Avram, Elena Irimia, Verginica Barbu Mititelu, Maria Mitrofan
The paper contains a detailed description of the acquisition process, corpus statistics as well as an evaluation of the corpus influence on a low-latency ASR system as well as a dialogue component.
no code implementations • LREC 2020 • Dan Tufi{\textcommabelow{s}}, Maria Mitrofan, Vasile P{\u{a}}i{\textcommabelow{s}}, Radu Ion, Andrei Coman
We present the Romanian legislative corpus which is a valuable linguistic asset for the development of machine translation systems, especially for under-resourced languages.
no code implementations • LREC 2020 • Tam{\'a}s V{\'a}radi, Svetla Koeva, Martin Yamalov, Marko Tadi{\'c}, B{\'a}lint Sass, Bart{\l}omiej Nito{\'n}, Maciej Ogrodniczuk, Piotr P{\k{e}}zik, Verginica Barbu Mititelu, Radu Ion, Elena Irimia, Maria Mitrofan, Vasile P{\u{a}}i{\textcommabelow{s}}, Dan Tufi{\textcommabelow{s}}, Radovan Garab{\'\i}k, Simon Krek, Andraz Repar, Matja{\v{z}} Rihtar, Janez Brank
This article presents the current outcomes of the MARCELL CEF Telecom project aiming to collect and deeply annotate a large comparable corpus of legal documents.
no code implementations • LREC 2020 • Vasile P{\u{a}}i{\textcommabelow{s}}, Radu Ion, Dan Tufi{\textcommabelow{s}}
This paper presents RELATE (http://relate. racai. ro), a high-performance natural language platform designed for Romanian language.
no code implementations • LREC 2020 • Vasile Pais, Radu Ion
This paper describes RACAI{'}s automatic term extraction system, which participated in the TermEval 2020 shared task on English monolingual term extraction.
no code implementations • LREC 2020 • Vasile Pais, Dan Tufi{\textcommabelow{s}}, Radu Ion
This paper describes RACAI{'}s word sense alignment system, which participated in the Monolingual Word Sense Alignment shared task organized at GlobaLex 2020 workshop.
no code implementations • WS 2019 • Radu Ion, Vasile Florian P{\u{a}}i{\textcommabelow{s}}, Maria Mitrofan
This paper describes the Named Entity Recognition system of the Institute for Artificial Intelligence {``}Mihai Dr{\u{a}}g{\u{a}}nescu{''} of the Romanian Academy (RACAI for short).
no code implementations • RANLP 2017 • Maria Mitrofan, Radu Ion
This paper presents the adaptation of the Hidden Markov Models-based TTL part-of-speech tagger to the biomedical domain.
no code implementations • LREC 2012 • Radu Ion, Elena Irimia, Dan {\c{S}}tef{\u{a}}nescu, Dan Tufi{\textcommabelow{s}}
This article describes the collecting, processing and validation of a large balanced corpus for Romanian.
no code implementations • LREC 2012 • Radu Ion
Extracting parallel data from comparable corpora in order to enrich existing statistical translation models is an avenue that attracted a lot of research in recent years.