Papers by Katsiaryna Mlynchyk
A Methodology for Creating Question Answering Corpora Using Inverse Data Annotation (2020.acl-main)
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Jan Deriu, Katsiaryna Mlynchyk, Philippe Schläpfer, Alvaro Rodrigo, Dirk von Grünigen, Nicolas Kaiser, Kurt Stockinger, Eneko Agirre, Mark Cieliebak
| Challenge: | Existing methods to efficiently construct corpus for question answering over structured data are time-consuming and cost-intensive. |
| Approach: | They propose a method to efficiently construct a corpus for question answering over structured data. |
| Outcome: | The proposed method triples the annotation speed while maintaining complexity of queries. |
Error-preserving Automatic Speech Recognition of Young English Learners’ Language (2024.acl-long)
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| Challenge: | State-of-the-art speech recognition models are often trained on adult read-aloud data by native speakers and do not transfer well to young language learners’ speech. |
| Approach: | They propose to use an automated speech recognition module to train language learners' speaking skills on spontaneous speech by young language learners. |
| Outcome: | The proposed model improves on 85 hours of English audio spoken by Swiss learners and preserves their mistakes. |