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Found 5 papers, 1 papers with code
Your Model Is Not Predicting Depression Well And That Is Why: A Case Study of PRIMATE Dataset
This paper addresses the quality of annotations in mental health datasets used for NLP-based depression level estimation from social media texts.
Enhancing Sequence-to-Sequence Neural Lemmatization with External Resources
We also compare with other methods of integrating external data into lemmatization and show that our enhanced system performs considerably better than a simple lexicon extension method based on the Stanza system, and it achieves complementary improvements w. r. t.
Evaluating Multilingual BERT for Estonian
Recently, large pre-trained language models, such as BERT, have reached state-of-the-art performance in many natural language processing tasks, but for many languages, including Estonian, BERT models are not yet available.
Automated Word Stress Detection in Russian
In this study we address the problem of automated word stress detection in Russian using character level models and no part-speech-taggers.
Char-RNN for Word Stress Detection in East Slavic Languages
We explore how well a sequence labeling approach, namely, recurrent neural network, is suited for the task of resource-poor and POS tagging free word stress detection in the Russian, Ukranian, Belarusian languages.
