EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 16 of its 78 references that are in the map. First posted on arXiv 28 Apr 2022.
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16 of 78 references.
References · 16
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4 more
- 2020Overview of the Ninth Dialog System Technology Challenge: DSTC9cited by 49
- 2020Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representationscited by 42
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2 papers.