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Found 7 papers, 1 papers with code
ParlaSpeech-HR - a Freely Available ASR Dataset for Croatian Bootstrapped from the ParlaMint Corpus
This paper presents our bootstrapping efforts of producing the first large freely available Croatian automatic speech recognition (ASR) dataset, 1, 816 hours in size, obtained from parliamentary transcripts and recordings from the ParlaMint corpus.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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MaCoCu: Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages
We introduce the project “MaCoCu: Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages”, funded by the Connecting Europe Facility, which is aimed at building monolingual and parallel corpora for under-resourced European languages.
Language Models on a Diet: Cost-Efficient Development of Encoders for Closely-Related Languages via Additional Pretraining
The world of language models is going through turbulent times, better and ever larger models are coming out at an unprecedented speed.
Do Language Models Care About Text Quality? Evaluating Web-Crawled Corpora Across 11 Languages
Large, curated, web-crawled corpora play a vital role in training language models (LMs).
The ParlaSent Multilingual Training Dataset for Sentiment Identification in Parliamentary Proceedings
The paper presents a new training dataset of sentences in 7 languages, manually annotated for sentiment, which are used in a series of experiments focused on training a robust sentiment identifier for parliamentary proceedings.
The ParlaSent-BCS dataset of sentiment-annotated parliamentary debates from Bosnia-Herzegovina, Croatia, and Serbia
A six-level schema is applied to the data with the aim of training a classification model for the detection of sentiment in parliamentary proceedings.
The GINCO Training Dataset for Web Genre Identification of Documents Out in the Wild
This paper presents a new training dataset for automatic genre identification GINCO, which is based on 1, 125 crawled Slovenian web documents that consist of 650 thousand words.
