Papers by Irina Temnikova

3 papers
The WAW Corpus: The First Corpus of Interpreted Speeches and their Translations for English and Arabic (L18-1)

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Challenge: Using the corpus, we study the characteristics of interpreters' work and train machine translation systems.
Approach: They propose to build an interpreting corpus for Arabic and an Arabic corpus to study interpreters' work.
Outcome: The proposed corpus can be used for teaching interpreters and to train machine translation systems.
Evaluating Pronominal Anaphora in Machine Translation: An Evaluation Measure and a Test Suite (D19-1)

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Challenge: Currently, machine translation is performed at the level of individual sentences, in isolation from the rest of the document.
Approach: They propose a dataset that can be used as a test suite for pronoun translation . they propose an evaluation measure to differentiate good and bad pronounce translations .
Outcome: The proposed dataset can be used as a test suite for pronoun translation in English . it covers multiple source languages and different pronouner errors drawn from real system translations .
SM-FEEL-BG - the First Bulgarian Datasets and Classifiers for Detecting Feelings, Emotions, and Sentiments of Bulgarian Social Media Text (2024.lrec-main)

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Challenge: SM-FEEL-BG is the first Bulgarian-language package for emotion detection and sentiment analysis.
Approach: They introduce SM-FEEL-BG, a Bulgarian-language package that contains 6 datasets with Social Media (SM) texts with emotion, feeling, and sentiment labels and 4 classifiers trained on them.
Outcome: The proposed package is the first to be released in Bulgarian and is available for free.

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