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Assamese WSD List
No full textWSD is the process of identifying the proper sense of an ambiguous word depending on the particular context. Assamese WSD list comprise of more than 100 words with their multiple senses. Also English meaning of each of the senses are given.
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1. These Assamese NLP resources including the Tools and Applications are developed
during Research and Development Projects as well as Masters and Ph.D. thesis
works.
2. These are mainly developed or generated at Gauhati University Department of
Computer Science and Department of Information Technology.
3. These resources are used by students and researchers for further studies, researches, as
well as for design and development of tools and applications.
4. Computational Linguistics in Assamese is not rich, and Natural Language Processing
works have mainly started during last two decades, and most of the resources are first
generation resources, and with ample scope for upgrading, enriching, and purifying.
5. These are very good and essential resources for all the researchers in Assamese NLP, as
the language requires more and more NLP works to make Assamese a rich media for
the digital world.
6. Anyone interested, or in need of such resources may express their interest for the
required resources, and the way of availability will be advised/informed accordingly.
7. These are purely research materials and could only be used for further research only.
8. Researchers may visit the NLP Lab of Department of Information Technology, Gauhati
University, Guwahati, India or contact us.
9. Researchers interested in collaborative works, and also students for project works, are
welcome.
10. Contact person is Professor Shikhar Kr. Sarma, Department of Information
Technology, Gauhati University, Guwahati 781014, Assam, India. Email-
[email protected]
Speech activity annotation for a subset of the Clarin-PL studio corpus
No full textThis is a hand-checked annotation of speech activity within a subset of the Clarin-PL studio corpus, containing 20 session with 619 recordings. This submission does not contain any audio files - these can be found either in the submission http://hdl.handle.net/11321/236, or under URL: http://mowa.clarin-pl.eu/korpus
PolEmo 2.0 Sentiment Analysis Dataset for CoNLL
No full textPolEmo 2.0: Corpus of Multi-Domain Consumer Reviews, evaluation data for article presented at CoNLL
Citation:
@inproceedings{kocon-etal-2019-multi,
title = "Multi-Level Sentiment Analysis of {P}ol{E}mo 2.0: Extended Corpus of Multi-Domain Consumer Reviews",
author = "Koco{\'n}, Jan and
Mi{\l}kowski, Piotr and
Za{\'s}ko-Zieli{\'n}ska, Monika",
booktitle = "Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)",
month = nov,
year = "2019",
address = "Hong Kong, China",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/K19-1092",
doi = "10.18653/v1/K19-1092",
pages = "980--991",
abstract = "In this article we present an extended version of PolEmo {--} a corpus of consumer reviews from 4 domains: medicine, hotels, products and school. Current version (PolEmo 2.0) contains 8,216 reviews having 57,466 sentences. Each text and sentence was manually annotated with sentiment in 2+1 scheme, which gives a total of 197,046 annotations. We obtained a high value of Positive Specific Agreement, which is 0.91 for texts and 0.88 for sentences. PolEmo 2.0 is publicly available under a Creative Commons copyright license. We explored recent deep learning approaches for the recognition of sentiment, such as Bi-directional Long Short-Term Memory (BiLSTM) and Bidirectional Encoder Representations from Transformers (BERT).",
Assamese Corpus
No full textAssamese Corpus was developed in the NLP Lab of Gauhati University. Total size of Assamese Corpus (in terms of words) is 1.6 million (1613551 words). The Corpus is prepared following the guidelines of Corpus Encoding Standard and is UNICODE encoded. Corpus for Assamese language was developed keeping in mind certain issues like- Size of the corpus, Genre or domain selection, Range of writers, data collection, Computerization of data, Validation of corpus. The types of genre/domain used in the corpus were- Literature, Learned-Material and Media which includes Newspapers.
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1. These Assamese NLP resources including the Tools and Applications are developed
during Research and Development Projects as well as Masters and Ph.D. thesis
works.
2. These are mainly developed or generated at Gauhati University Department of
Computer Science and Department of Information Technology.
3. These resources are used by students and researchers for further studies, researches, as
well as for design and development of tools and applications.
4. Computational Linguistics in Assamese is not rich, and Natural Language Processing
works have mainly started during last two decades, and most of the resources are first
generation resources, and with ample scope for upgrading, enriching, and purifying.
5. These are very good and essential resources for all the researchers in Assamese NLP, as
the language requires more and more NLP works to make Assamese a rich media for
the digital world.
6. Anyone interested, or in need of such resources may express their interest for the
required resources, and the way of availability will be advised/informed accordingly.
7. These are purely research materials and could only be used for further research only.
8. Researchers may visit the NLP Lab of Department of Information Technology, Gauhati
University, Guwahati, India or contact us.
9. Researchers interested in collaborative works, and also students for project works, are
welcome.
10. Contact person is Professor Shikhar Kr. Sarma, Department of Information
Technology, Gauhati University, Guwahati 781014, Assam, India. Email-
[email protected]
Nawałka
Get PDFPrzeprowadzenie badań w celu analizy nad tematem pracy magisterskiej na temat "Wizerunek trenera piłki nożnej
Assamese Multi Word Expressions
No full textMultiword Expressions are sequence of words, separated by space delimiter (or any) which determines a unique meaning instead of words' individual meanings. A list comprising of 927 Multi-word Expressions have been identified for Assamese language. Example of the Assamese MWEs are “মাটিৰ মানুহ”, “ খটক খটক ” etc
Assamese-English Bilingual Dictionary
No full textThe Bilingual dictionary is created for Assamese-English.. In the Bilingual dictionary English meaning of Assamese words are given with POS of the words.
---
1. These Assamese NLP resources including the Tools and Applications are developed
during Research and Development Projects as well as Masters and Ph.D. thesis
works.
2. These are mainly developed or generated at Gauhati University Department of
Computer Science and Department of Information Technology.
3. These resources are used by students and researchers for further studies, researches, as
well as for design and development of tools and applications.
4. Computational Linguistics in Assamese is not rich, and Natural Language Processing
works have mainly started during last two decades, and most of the resources are first
generation resources, and with ample scope for upgrading, enriching, and purifying.
5. These are very good and essential resources for all the researchers in Assamese NLP, as
the language requires more and more NLP works to make Assamese a rich media for
the digital world.
6. Anyone interested, or in need of such resources may express their interest for the
required resources, and the way of availability will be advised/informed accordingly.
7. These are purely research materials and could only be used for further research only.
8. Researchers may visit the NLP Lab of Department of Information Technology, Gauhati
University, Guwahati, India or contact us.
9. Researchers interested in collaborative works, and also students for project works, are
welcome.
10. Contact person is Professor Shikhar Kr. Sarma, Department of Information
Technology, Gauhati University, Guwahati 781014, Assam, India. Email-
[email protected]
ELMo Embeddings for Polish
No full textA model of ELMo embeddings for Polish language trained on large textual corpora (KGR10). To retrain the model please use the checkpoint and vocabulary files available at: https://nextcloud.clarin-pl.eu/index.php/s/EV96cjfflKwt2x
