Publication type: Conference paper
Type of review: Peer review (abstract)
Title: LIHLITH : learning to interact with humans by lifelong interaction with humans
Authors: Agirre, Eneko
Otegi, Arantxa
Pradel, Camille
Rosset, Sophie
Peñas, Anselmo
Cieliebak, Mark
et. al: No
Conference details: SEPLN2019, Bilbao, Spain, September 25-27, 2019
Issue Date: 2019
Language: English
Subject (DDC): 004: Computer science
Abstract: The LIHLITH project will research, innovate and validate a new lifelong learning framework for the interaction of humans and machines on specific domains with the aim of improving the quality of existing dialogue systems and lowering the cost of deployment in new domains. LILITH will develop dialogue systems that learn autonomously from their interactions with the users, and retain this new knowledge in order to answer more accurately in future interactions. The key insight is that the dialogue systems will be designed to get feedback from the user. Based on this feedback, the system will keep improving after deployment all modules down in the pipeline. LIHLITH project will also develop and deliver evaluation protocols and benchmarks to allow public comparison and reproducibility.
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Applied Information Technology (InIT)
Appears in collections:Publikationen School of Engineering

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