Generating Genre-Specific Musical Transcriptions of Antonín Dvořák through a Variational Autoencoder
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14210%2F21%3A00123177" target="_blank" >RIV/00216224:14210/21:00123177 - isvavai.cz</a>
Result on the web
<a href="https://digilib.phil.muni.cz/handle/11222.digilib/111872" target="_blank" >https://digilib.phil.muni.cz/handle/11222.digilib/111872</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5817/MB2021-2-5" target="_blank" >10.5817/MB2021-2-5</a>
Alternative languages
Result language
čeština
Original language name
Generování žánrově specifické hudební transkripce Antonína Dvořáka prostřednictvím variačního autoenkodéru
Original language description
Apart from traditional deep learning tasks such as pattern recognition, stock price prediction, and machine translation, this method also finds practical application within algorithmic composition. This paper explores the use of a generative model based on unsupervised learning of a musical style from a pre-selected corpus and the subsequent prediction of samples from the estimated distribution. The model uses a Long Short-Term Memory neural network whose training data contains genre-specific melodies in symbolic representation.
Czech name
Generování žánrově specifické hudební transkripce Antonína Dvořáka prostřednictvím variačního autoenkodéru
Czech description
Apart from traditional deep learning tasks such as pattern recognition, stock price prediction, and machine translation, this method also finds practical application within algorithmic composition. This paper explores the use of a generative model based on unsupervised learning of a musical style from a pre-selected corpus and the subsequent prediction of samples from the estimated distribution. The model uses a Long Short-Term Memory neural network whose training data contains genre-specific melodies in symbolic representation.
Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
60403 - Performing arts studies (Musicology, Theater science, Dramaturgy)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Musicologica Brunensia
ISSN
1212-0391
e-ISSN
2336-436X
Volume of the periodical
56
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
13
Pages from-to
49-61
UT code for WoS article
000766749800005
EID of the result in the Scopus database
2-s2.0-85128758860