Papers by Michał Lis

2 papers
EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification (2022.findings-naacl)

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Challenge: Knowledge-based authentication is crucial for task-oriented spoken dialogue systems that offer personalised and privacy-focused services . e-learning systems should be able to enrol, identify, and verify new and recurring users based on their personal information .
Approach: They propose to formalise three authentication tasks and their evaluation protocols . they propose to use a spoken multilingual dataset with 5,506 spoken dialogues .
Outcome: The proposed models set the first competitive benchmarks and set directions for future research.
Multilingual and Cross-Lingual Intent Detection from Spoken Data (2021.emnlp-main)

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Challenge: a systematic study on multilingual and cross-lingual intent detection from spoken data is presented . current work on intent detection is limited to English, and standard benchmarks exist only in English.
Approach: They present a systematic study on multilingual and cross-lingual intent detection from spoken data.
Outcome: The proposed resource is called MInDS-14, and it provides strong intent detection in most target languages.

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