Pisanje tekstova pjesama putem strojnog učenja

master's thesis

• Title (english): Machine Learning for Songwriting
• Author: Dominik Domović
• Mentor: Vladimir Čeperić (mentor)
• Committee member: Vladimir Čeperić (predsjednik povjerenstva)
• Committee member: Slobodan Ribarić (član povjerenstva)
• Committee member: Goran Delač (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2019-07-19, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Ovaj diplomski rad ukratko objašnjava osnove strojnog učenja i neuronskih mreža, te pokriva elemente strojnog učenja potrebnih za ovaj rad. U sklopu rada razvijen je program čija je zadaća naučiti stil pisanja pjesama nekog autora, te na temelju toga generirati novu pjesmu. Pokazani su rezultati traženja optimalnih parametara, rezultati pri treniranju, te primjer konačno generirane pjesme. Također se provodi usporedba s prijašnjim radom. Zaključuje se da program može uspješno naučiti specifičan stil pisanja pjesama, nakon pronalaženja optimalnih parametara.

Abstract (english)

The master's thesis briefly explains the basics of machine learning and neural networks, as well as other elements used in the thesis. As a part of the thesis, a program has been developed that has a task of learning the art style of a specific author, and then generate a song. Results of searching for the optimal parameters have been displayed, as well as training results, and, finally, an example of a generated song. A comparison is also made with the author's earlier work. It is concluded that the program can successfully learn to copy the art style, after it finds the optimal parameters.

• Keywords: strojno učenje; neuronske mreže; neuron; k-fold; RNN; LSTM; generiranje pjesama
• Keywords (english): machine learning; neural networks; neuron; k-fold; RNN; LSTM; lyrics generation
• Language: croatian
• URN:NBN: urn:nbn:hr:168:246320
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2020-01-07 17:39:00