| 1 |
An Overview of Indian Spoken Language Recognition from Machine Learning Perspective
|
|
|
|
In: ISSN: 2375-4699 ; EISSN: 2375-4702 ; ACM Transactions on Asian and Low-Resource Language Information Processing ; https://hal.inria.fr/hal-03616853 ; ACM Transactions on Asian and Low-Resource Language Information Processing, ACM, In press, ⟨10.1145/3523179⟩ (2022)
|
|
BASE
|
|
Show details
|
|
|
| 2 |
Speech Perception and Implementation in a Virtual Medical Assistant
|
|
|
|
In: 6. ICAART – 14th International Conference on Agents and Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-03621550 ; 6. ICAART – 14th International Conference on Agents and Artificial Intelligence, Feb 2022, Vienna, Austria (2022)
|
|
BASE
|
|
Show details
|
|
|
| 3 |
Assessing the impact of OCR noise on multilingual event detection over digitised documents
|
|
|
|
In: ISSN: 1432-5012 ; EISSN: 1432-1300 ; International Journal on Digital Libraries ; https://hal.archives-ouvertes.fr/hal-03635985 ; International Journal on Digital Libraries, Springer Verlag, 2022, ⟨10.1007/s00799-022-00325-2⟩ (2022)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
Introducing the HIPE 2022 Shared Task: Named Entity Recognition and Linking in Multilingual Historical Documents
|
|
|
|
In: Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II ; https://hal.archives-ouvertes.fr/hal-03635971 ; Matthias Hagen; Suzan Verberne; Craig Macdonald; Christin Seifert; Krisztian Balog; Kjetil Nørvåg; Vinay Setty. Advances in Information Retrieval. 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10–14, 2022, Proceedings, Part II, 13186, Springer International Publishing, pp.347-354, 2022, Lecture Notes in Computer Science, 978-3-030-99738-0. ⟨10.1007/978-3-030-99739-7_44⟩ (2022)
|
|
Abstract:
International audience ; We present the HIPE-2022 shared task on named entity processing in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 evaluation lab, this edition confronts systems with the challenges of dealing with more languages, learning domain-specific entities, and adapting to diverse annotation tag sets. HIPE-2022 is part of the ongoing efforts of the natural language processing and digital humanities communities to adapt and develop appropriate technologies to efficiently retrieve and explore information from historical texts. On such material, however, named entity processing techniques face the challenges of domain heterogeneity, input noisiness, dynamics of language, and lack of resources. In this context, the main objective of the evaluation lab is to gain new insights into the transferability of named entity processing approaches across languages, time periods, document types, and annotation tag sets.
|
|
Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; [INFO.INFO-DL]Computer Science [cs]/Digital Libraries [cs.DL]; [INFO.INFO-HC]Computer Science [cs]/Human-Computer Interaction [cs.HC]; [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]; [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; digital humanities; historical documents; information extraction; named entity processing; text understanding
|
|
URL: https://hal.archives-ouvertes.fr/hal-03635971
https://hal.archives-ouvertes.fr/hal-03635971/file/HIPE2022_ECIR_shortpaper_postprint.pdf
https://hal.archives-ouvertes.fr/hal-03635971/document
https://doi.org/10.1007/978-3-030-99739-7_44
|
|
BASE
|
|
Hide details
|
|
|
|
|
