Music Playlist Title Generation: A Machine-Translation Approach
- URL: http://arxiv.org/abs/2110.07354v1
- Date: Sun, 3 Oct 2021 04:39:39 GMT
- Title: Music Playlist Title Generation: A Machine-Translation Approach
- Authors: SeungHeon Doh, Junwon Lee, Juhan Nam
- Abstract summary: We propose a machine-translation approach to automatically generate a playlist title from a set of music tracks.
We take a sequence of track IDs as input and a sequence of words in a playlist title as output.
Considering the orderless nature of music tracks in a playlist, we propose two techniques that remove the order of the input sequence.
- Score: 6.7034293304862755
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We propose a machine-translation approach to automatically generate a
playlist title from a set of music tracks. We take a sequence of track IDs as
input and a sequence of words in a playlist title as output, adapting the
sequence-to-sequence framework based on Recurrent Neural Network (RNN) and
Transformer to the music data. Considering the orderless nature of music tracks
in a playlist, we propose two techniques that remove the order of the input
sequence. One is data augmentation by shuffling and the other is deleting the
positional encoding. We also reorganize the existing music playlist datasets to
generate phrase-level playlist titles. The result shows that the Transformer
models generally outperform the RNN model. Also, removing the order of input
sequence improves the performance further.
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