MaCmS: Magahi Code-mixed Dataset for Sentiment Analysis

Autor: Rani, Priya, Negi, Gaurav, Fransen, Theodorus, McCrae, John P.

The present paper introduces new sentiment data, MaCMS, for Magahi-Hindi-English (MHE) code-mixed language, where Magahi is a less-resourced minority language. This dataset is the first Magahi-Hindi-English code-mixed dataset for sentiment analysis t

Externí odkaz: http://arxiv.org/abs/2403.04639

Findings of the LoResMT 2021 Shared Task on COVID and Sign Language for Low-resource Languages

Autor: Ojha, Atul Kr., Liu, Chao-Hong, Kann, Katharina, Ortega, John, Shatam, Sheetal, Fransen, Theodorus

We present the findings of the LoResMT 2021 shared task which focuses on machine translation (MT) of COVID-19 data for both low-resource spoken and sign languages. The organization of this task was conducted as part of the fourth workshop on technolo

Externí odkaz: http://arxiv.org/abs/2108.06598

A Multilingual Evaluation Dataset for Monolingual Word Sense Alignment

Autor: Ahmadi, Sina, McCrae, John P., Nimb, Sanni, Troelsgård, Thomas, Olsen, Sussi, Pedersen, Bolette S., Declerck, Thierry, Wissik, Tanja, Monachini, Monica, Bellandi, Andrea, Khan, Fahad, Pisani, Irene, Krek, Simon, Lipp, Veronika, Váradi, Tamás, Simon, László, Győrffy, András, Tiberius, Carole, Schoonheim, Tanneke, Moshe, Yifat Ben, Rudich, Maya, Ahmad, Raya Abu, Dorielle Lonke, Kovalenko, Kira, Langemets, Margit, Kallas, Jelena, Dereza, Oksana, Fransen, Theodorus, Cillessen, David, Lindemann, David, Alonso, Mikel, Salgado, Ana, Sancho, José Luis, Rafael-J. Ureña-Ruiz, Simov, Kiril, Osenova, Petya, Kancheva, Zara, Radev, Ivaylo, Stanković, Ranka, Krstev, Cvetana, Lazić, Biljana, Marković, Aleksandra, Perdih, Andrej, Gabrovšek, Dejan

Aligning senses across resources and languages is a challenging task with beneficial applications in the field of natural language processing and electronic lexicography. In this paper, we describe our efforts in manually aligning monolingual diction

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0494fc2941f2fa3a520a46349d894974
https://doi.org/10.5281/zenodo.3842647

A Comparative Study of Different State-of-the-Art Hate Speech Detection Methods in Hindi-English Code-Mixed Data

Autor: Rani, Priya, Shardul Suryawanshi, Koustava Goswami, Bharathi Raja Chakravarthi, Fransen, Theodorus, McCrae, John Philip

Publikováno v: Second Workshop on Trolling, Aggression and Cyberbullying at LREC 2020

Hate speech detection in social media communication has become one of the primary concerns to avoid conflicts and curb undesired activities. In an environment where multilingual speakers switch among multiple languages, hate speech detection becomes

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68d1a9a0db73dab1fd7932ed2e2917b4

Developing automatic speech recognition for Scottish Gaelic

Autor: Evans, Lucy, Lamb, William, Sinclair, Mark, Alex, Beatrice

Publikováno v: Evans, L, Lamb, W, Sinclair, M & Alex, B 2022, Developing automatic speech recognition for Scottish Gaelic . in T Fransen, W Lamb & D Prys (eds), Proceedings of the 4th Celtic Language Technology Workshop at LREC 2022 (CLTW 4) . pp. 110-120, The 4th Celtic Language Technology Workshop at LREC 2022, Marseille, France, 20/06/22 . < http://www.lrec-conf.org/proceedings/lrec2022/workshops/CLTW4/index.html >

This paper discusses our efforts to develop a full automatic speech recognition (ASR) system for Scottish Gaelic, starting froma point of limited resource. Building ASR technology is important for documenting and revitalising endangered languages;it

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______3094::7f7520b207204f1580b8f78e4939cccb
https://hdl.handle.net/20.500.11820/f1409d74-e8e6-4c59-99e2-9f3f0dd80b1e