Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bagdat Myrzakhmetov"'
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783031243363
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e7cb1b5f9d150e6dad2816fed7b9cc3
https://doi.org/10.1007/978-3-031-24337-0_26
https://doi.org/10.1007/978-3-031-24337-0_26
Publikováno v:
2019 IEEE 13th International Conference on Application of Information and Communication Technologies (AICT).
In this paper we present work on intelligent multimodal search and archive system, in which the scientific findings obtained in the work on recognition of Kazakh and Russian speeches, language identification and spoken term detection methods were app
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::432d1d1ea8e8a3dedc0b68329b9c09a6
https://doi.org/10.1109/aict47866.2019.8981781
https://doi.org/10.1109/aict47866.2019.8981781
Autor:
Bagdat Myrzakhmetov, Aibek Makazhanov
Publikováno v:
Research in Computing Science. 117:153-160
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f1176d9a6f8a8669e27ec8fd20430b2
https://doi.org/10.13053/rcs-117-1-13
https://doi.org/10.13053/rcs-117-1-13
Publikováno v:
2018 IEEE 12th International Conference on Application of Information and Communication Technologies (AICT).
We address the problem of normalizing user generated content in a multilingual setting. Specifically, we target comment sections of popular Kazakhstani Internet news outlets, where comments almost always appear in Kazakh or Russian, or in a mixture o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::375a9a1717a13f8286bf28de88781e5b
https://doi.org/10.1109/icaict.2018.8747161
https://doi.org/10.1109/icaict.2018.8747161
Publikováno v:
2017 IEEE 11th International Conference on Application of Information and Communication Technologies (AICT).
In this exploratory study we attempt to draw parallels between so called dimensions of Big Data (i.e. Volume, Veracity, Variety, Velocity, or 4V -s) and various aspects of machine translation. For this purpose we set up a number of experiments that i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec74d8d04be77cd8e9075f73eae1cf10
https://doi.org/10.1109/icaict.2017.8687000
https://doi.org/10.1109/icaict.2017.8687000
Publikováno v:
EMNLP
Syllabification does not seem to improve word-level RNN language modeling quality when compared to character-based segmentation. However, our best syllable-aware language model, achieving performance comparable to the competitive character-aware mode
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::de0a0e609e607d48795671488dea7587
http://arxiv.org/abs/1707.06480
http://arxiv.org/abs/1707.06480