Wyniki wyszukiwania - BazTech

Ograniczanie wyników

Znaleziono wyników: 2

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: part of speech

Sortuj według:

Ogranicz wyniki do:

Deep learning based Tamil Parts of Speech (POS) tagger

Anbukkarasi S., Varadhaganapathy S.

Bulletin of the Polish Academy of Sciences. Technical Sciences

2021

Vol. 69, nr 6

art. no. e138820

This paper addresses the problem of part of speech (POS) tagging for the Tamil language, which is low resourced and agglutinative. POS tagging is the process of assigning syntactic categories for the words in a sentence. This is the preliminary step for many of the Natural Language Processing (NLP) tasks. For this work, various sequential deep learning models such as recurrent neural network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU) and Bi-directional Long Short-Term Memory (Bi-LSTM) were used at the word level. For evaluating the model, the performance metrics such as precision, recall, F1-score and accuracy were used. Further, a tag set of 32 tags and 225 000 tagged Tamil words was utilized for training. To find the appropriate hidden state, the hidden states were varied as 4, 16, 32 and 64, and the models were trained. The experiments indicated that the increase in hidden state improves the performance of the model. Among all the combinations, Bi-LSTM with 64 hidden states displayed the best accuracy (94%). For Tamil POS tagging, this is the initial attempt to be carried out using a deep learning model.

Slovak Morphosyntactic Tagset

Garabík R., Šimková M.

Journal of Language Modelling

2012

Vol. 0, No. 1

41--63

Morphological annotation constitutes essential, very useful and very common linguistic information presented in corpora, especially for highly inflectional languages. The morphological tagset used in the Slovak National Corpus has been designed with several goals in mind – the tags are compact and easily human-readable, without sacrificing their informational contents. The tags consist of ASCII letters, numbers and several other characters. In general, they have a variable numer of symbols, but their order is obligatory, and each category or specific feature is assigned a particular character, which can be shared among several parts of speech. The tagset is highly functional and pragmatic, although some allowances had to be made to accommodate the traditional analysis of Slovak morphology and part of speech categories.