%0 Conference Proceedings
%T Greek Lyrics Generation
%+ School of Informatics [Thessaloniki]
%A Lampridis, Orestis
%A Kefalas, Athanasios
%A Tzallas, Petros
%Z Part 7: Natural Language
%< avec comité de lecture
%@ 978-3-030-49185-7
%( IFIP Advances in Information and Communication Technology
%B 16th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI)
%C Neos Marmaras, Greece
%Y Ilias Maglogiannis
%Y Lazaros Iliadis
%Y Elias Pimenidis
%I Springer International Publishing
%3 Artificial Intelligence Applications and Innovations
%V AICT-584
%N Part II
%P 445-454
%8 2020-06-05
%D 2020
%R 10.1007/978-3-030-49186-4_37
%K Lyrics generation;Natural language processing;Machine learning
%Z Computer Science [cs]Conference papers
%X This paper documents the efforts in implementing lyric generation machine learning models in the Greek language for the genre of Éntekhno music. To accomplish this, we used three different Long Short-Term Memory Recurrent Neural Network approaches. The first method utilizes word-level bi-directional network models, the second method expands on the first by learning the word embeddings on the initial layer of the network, while the last method is based on a char-level network model. Our experimental procedure, which utilized a high sample of human judges, shows that texts of lyrics generated by our models are of high quality and are not that easily distinguishable from actual lyrics.
%G English
%Z TC 12
%Z WG 12.5
%2 https://inria.hal.science/hal-04060663/document
%2 https://inria.hal.science/hal-04060663/file/500087_1_En_37_Chapter.pdf
%L hal-04060663
%U https://inria.hal.science/hal-04060663
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-584