Please use this identifier to cite or link to this item: http://artemis.cslab.ece.ntua.gr:8080/jspui/handle/123456789/17682
Full metadata record
DC FieldValueLanguage
dc.contributor.authorVasilopoulos, Emmanouil-
dc.date.accessioned2020-09-28T06:47:19Z-
dc.date.available2020-09-28T06:47:19Z-
dc.date.issued2020-09-03-
dc.identifier.urihttp://artemis.cslab.ece.ntua.gr:8080/jspui/handle/123456789/17682-
dc.description.abstractThe purpose of this thesis is the design and implementation of a system that automates the process of mixing music. Widely used services such as Spotify and Apply Music provide playlists grouped by genre, date of release etc. They do not provide the ability of unifying the music and the reproduction of the songs with harmony or continuity. The same applies for the commonly used media players. The system designed receives in its input a play-list and it produces in its output the proper signals the control a dj software. The method we followed uses the detection of points in time of a song using Artificial Neural Networks. The research of the thesis is based on this problem, with the best results given by a Convolutional Neural Network, in combination with the proper data representation. The predicted points given by the A.N.N. are used by a second system that automates the basic technic that deejays use to transition from the current song playing to the next. The final conclusion, regarding the detection of points in time, is the significance of the form of the input and more importantly of the output, during the training phase, with the architecture contributing to the optimization of the system.en_US
dc.languageelen_US
dc.subjectNeural Networksen_US
dc.subjectMusicen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectdeejayen_US
dc.subjectConvolutionalen_US
dc.subjectSpectrogramen_US
dc.subjectmidien_US
dc.subjectdjen_US
dc.titleMixing Songs with the use of Neural Networksen_US
dc.description.pages104en_US
dc.contributor.supervisorΣτάμου Γιώργοςen_US
dc.departmentΤομέας Τεχνολογίας Πληροφορικής και Υπολογιστώνen_US
Appears in Collections:Διπλωματικές Εργασίες - Theses

Files in This Item:
File Description SizeFormat 
Emmanouil_Vasilopoulos_Thesis.pdf4.17 MBAdobe PDFView/Open


Items in Artemis are protected by copyright, with all rights reserved, unless otherwise indicated.