dc.contributor.author | Kao, Sheng | |
dc.contributor.author | Ilmini, Kalani | |
dc.date.accessioned | 2020-12-31T20:10:48Z | |
dc.date.available | 2020-12-31T20:10:48Z | |
dc.date.issued | 2020 | |
dc.identifier.uri | http://ir.kdu.ac.lk/handle/345/2934 | |
dc.description.abstract | Abstract: This paper discusses the
approaches involved in implementing
automated song lyrics system in the Sinhala
language. Which includes an overview of the
complexity of writing song lyrics and develop
an automated application for Sinhala song
lyrics generation. Before the implementation
was carried out, a set of Sinhala song lyrics
has been collected to create a corpus, and it
has been used to develop an RNN model with
LSTM layers using different temperatures
and epochs. Then the created models were
used to carry out a comparison process to
evaluate the effect of the corpus size and the
number of epochs per model training to get a
better understanding of the RNN training
behaviors. Finally, the system was served to
a web host to give the user a friendly UI,
where the user can enter desired keywords
and generate new Sinhala song lyrics. The
initial results were obtained through
different models and we could see that with
the increment of the number of epochs and
the number of song lyrics that are trained in
each model, the generated output had a clear
growth in terms of accuracy and meaning of
the song. | en_US |
dc.language.iso | en | en_US |
dc.subject | Recurrent Neural Networks | en_US |
dc.subject | Deep Learning | en_US |
dc.subject | Lyrics Generation | en_US |
dc.subject | LSTM | en_US |
dc.title | Automated Generation of Sinhala Lyrics using Recurrent Neural Networks | en_US |
dc.type | Article Full Text | en_US |
dc.identifier.journal | 13th International Research Conference General Sir John Kotelawala Defence University | en_US |
dc.identifier.pgnos | 96-106 | en_US |