Sign inGet started
Paper · arXiv

StarDrinks: An English and Korean Test Set for SLU Evaluation in a Drink Ordering Scenario

LLMs and speech assistants are increasingly used for task-oriented interactions, yet their evaluation often relies on controlled scenarios that fail to capture the variability and complexity of real user requests. Drink ordering, for example, involves diverse named entities, drink types, sizes, customizations, and brand-specific terminology, as well as spontaneous speech phenomena such as hesitations and self-corrections. To address this gap, we introduce StarDrinks, a test set in English and Korean containing speech utterances features, transcriptions, and annotated slots. Our dataset supports speech-to-slots SLU, transcription-to-slots NLU, and speech-to-transcription ASR evaluation, pr...

AuthorsMarcely Zanon Boito, Caroline Brun, Inyoung Kim et al.
Primary categorycs.CL
Published29 April 2026
Last updated at source3 July 2026
cs.CL
Embed this entry
<iframe src="https://silytics.si/embed/item/ab69e013-aadb-48d5-9cff-a433015b39a9" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.