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EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification
Georgios P. Spithourakis, Ivan Vulić, Michał Lis, Iñigo Casanueva, Paweł Budzianowski
Knowledge-based authentication is crucial for task-oriented spoken dialogue systems that offer personalised and privacy-focused services. Such systems should be able to enrol (E), verify (V), and identify (I) new and recurring users based on their personal information, e.g. postcode, name, and date of birth. In this work, we formalise the three authentication tasks and their evaluation protocols, and we present EVI, a challenging spoken multilingual dataset with 5,506 dialogues in English, Polish, and French. Our proposed models set the first competitive benchmarks, explore the challenges of multilingual natural language processing of spoken dialogue, and set directions for future research.
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Speaker Identification | EVI en-GB | Fuzzy Retrieval | Top-1 (%) | 67.77 | #1 of 1 | Archive leaderboard | report |
| Speaker Identification | EVI fr-FR | Fuzzy Retrieval | Top-1 (%) | 80.83 | #1 of 1 | Archive leaderboard | report |
| Speaker Identification | EVI pl-PL | Fuzzy Retrieval | Top-1 (%) | 95.13 | #1 of 1 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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