Isolating the singing voice from music tracks: a deep neural networks approach to karaoke

Jonathan Deboosere
Het isoleren van zang/instrumenten uit muziek aan de hand van artificiële intelligentie. Hierbij werd onderzoek gedaan naar een nieuwe methode om audio om te zetten in een formaat dat het menselijk gehoor beter representeert en er bijgevolg voor zorgt dat de computer betere voorspellingen kan maken.

Zang Isoleren uit Muziek aan de hand van Artificiële Intelligentie

Er is geen ontkomen aan, artificiële intelligentie (A.I.) is veelbelovend en wordt reeds in verschillende sectoren gebruikt. A.I. heeft o.a. zijn werking al bewezen bij het herkennen van gezichten en voorwerpen in afbeeldingen. Ook bij audio wordt er al gebruik van gemaakt. Je kunt bijvoorbeeld commando's geven aan je smartphone met je stem. Hiervoor wordt de audio omgezet in een bepaald formaat waaruit de computer kan leren. We maken er a.h.w. een soort afbeelding van. 

In deze thesis is onderzocht of computers kunnen leren om zang/instrumenten van muziek te isoleren. Ook hier wordt de audio eerst omgezet in een leesbaar formaat voor de computer. De computer maakt vervolgens een voorspelling van enkel de zang/instrumenten.

Het splitsen van zang en instrumenten uit een muziek track visueel voorgesteld

Ik onderzocht een nieuwe methode waarbij de audio wordt omgezet in een formaat dat het menselijk gehoor op een betere manier representeert. Uit de resultaten blijkt dat computer meer tijd nodig heeft om uit dit formaat te leren, maar de resultaten zijn veelbelovend.

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Universiteit of Hogeschool
Burgerlijk Ingenieur Computerwetenschappen
Publicatiejaar
2018
Promotor(en)
Tijl De Bie, Thomas Demeester
Kernwoorden