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Abstracts from the KAS corpus KAS-Abs 2.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
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2
The CLASSLA-StanfordNLP model for lemmatisation of standard Slovenian 1.4
Ljubešić, Nikola; Krsnik, Luka. - : Jožef Stefan Institute, 2022
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3
Corpus of academic Slovene KAS 2.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
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4
The Twitter user dataset for discriminating between Bosnian, Croatian, Montenegrin and Serbian Twitter-HBS 1.0
Ljubešić, Nikola; Rupnik, Peter. - : Jožef Stefan Institute, 2022
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5
Summarization datasets from the KAS corpus KAS-Sum 1.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
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6
Machine Translation datasets from the KAS corpus KAS-MT 1.0
Žagar, Aleš; Kavaš, Matic; Robnik-Šikonja, Marko. - : Faculty of Electrical Engineering and Computer Science, University of Maribor, 2022. : Faculty of Computer and Information Science, University of Ljubljana, 2022
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7
ASR training dataset for Croatian ParlaSpeech-HR v1.0
Abstract: The ParlaSpeech-HR dataset is built from parliamentary proceedings available in the Croatian part of the ParlaMint corpus and the parliamentary recordings available from the Croatian Parliament's YouTube channel. The corpus consists of segments 8-20 seconds in length. There are two transcripts available: the original one, and the one normalised via a simple rule-based normaliser. Each of the transcripts contains word-level alignments to the recordings. Each segment has a reference to the ParlaMint 2.1 corpus (http://hdl.handle.net/11356/1432) via utterance IDs. If a segment is based on a single utterance, speaker information for that segment is available as well. There is speaker information available for 381,849 segments, i.e., 95% of all segments. Speaker information consists of all the speaker information available from the ParlaMint 2.1 corpus (name, party, gender, age, status, role). There are all together 309 speakers in the dataset. The dataset is divided into a training, a development, and a testing subset. Development data consist of 500 segments coming from the 5 most frequent speakers, with the goal of not losing speaker variety on dev data. Test data consist of 513 segments that come from 3 male (258 segments) and 3 female speakers (255 segments). There are no segments coming from the 6 test speakers in the two remaining subsets. The 22,076 instances not having speaker information are not assigned to any of the three subsets. The remaining 380,836 instances form the training set.
Keyword: automatic speech recognition; parliamentary debates; speech database; speech recognition; speech recordings; speech transcription
URL: http://hdl.handle.net/11356/1494
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8
The news dataset for discriminating between Bosnian, Croatian and Serbian SETimes.HBS 1.0
Ljubešić, Nikola; Rupnik, Peter. - : Jožef Stefan Institute, 2022
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9
The CLASSLA-StanfordNLP model for morphosyntactic annotation of standard Slovenian 1.3
Ljubešić, Nikola; Krsnik, Luka. - : Jožef Stefan Institute, 2022
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10
The GINCO Training Dataset for Web Genre Identification of Documents Out in the Wild ...
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11
Geographic Adaptation of Pretrained Language Models ...
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12
The ParlaMint corpora of parliamentary proceedings
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13
Retweet communities reveal the main sources of hate speech
In: PLoS One (2022)
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14
The ParlaMint corpora of parliamentary proceedings
In: Lang Resour Eval (2022)
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15
Universal Dependencies 2.9
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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16
Universal Dependencies 2.8.1
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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17
Universal Dependencies 2.8
Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021
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18
Choice of plausible alternatives dataset in Croatian COPA-HR
Ljubešić, Nikola. - : Jožef Stefan Institute, 2021
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19
Croatian corpus of non-professional written language by typical speakers and speakers with language disorders RAPUT 1.0
Kuvač Kraljević, Jelena; Hržica, Gordana; Štefanec, Vanja. - : Jožef Stefan Institute, 2021. : Faculty of Education and Rehabilitation, University of Zagreb, 2021
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20
The Orange workflow for observing collocation trends ColTrend 1.0
Kosem, Iztok; Krek, Simon; Čibej, Jaka. - : Centre for Language Resources and Technologies, University of Ljubljana, 2021
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