Paper Abstract and Keywords |
Presentation |
2023-06-24 13:50
[Short Paper]
SBERT-based Musical Components Estimation from Lyrics Trained with Imbalanced "Orpheus" Data Mastuti Puspitasari, Takuya Takahashi (UEC), Gen Hori (AU), Shigeki Sagayama, Toru Nakashika (UEC) SP2023-18 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
This research was done to develop neural models that are capable of estimating appropriate musical components based on lyrics input. We extracted paired data of lyrics and musical components from “Orpheus”, a Japanese automated composition system with over 6000 user-published songs on the platform and used them as training data. These lyrics are converted into text embeddings with Sentence-BERT and then fed into neural models with their respective musical components for training. The imbalance in the data is mitigated by using focal loss to avoid overfitting and the performance of our models are evaluated subjectively through a survey. These models can be implemented in automated composition system to provide automated setup recommendation for the users and or used as a source of
inspiration in conventional composition. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Neural models / musical components / lyrics / Orpheus / automated composition / text embeddings / Sentence-BERT / focal loss |
Reference Info. |
IEICE Tech. Rep., vol. 123, no. 88, SP2023-18, pp. 86-90, June 2023. |
Paper # |
SP2023-18 |
Date of Issue |
2023-06-16 (SP) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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SP2023-18 |
Conference Information |
Committee |
SP IPSJ-MUS IPSJ-SLP |
Conference Date |
2023-06-23 - 2023-06-24 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
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Topics (in Japanese) |
(See Japanese page) |
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Paper Information |
Registration To |
SP |
Conference Code |
2023-06-SP-MUS-SLP |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
SBERT-based Musical Components Estimation from Lyrics Trained with Imbalanced "Orpheus" Data |
Sub Title (in English) |
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Keyword(1) |
Neural models |
Keyword(2) |
musical components |
Keyword(3) |
lyrics |
Keyword(4) |
Orpheus |
Keyword(5) |
automated composition |
Keyword(6) |
text embeddings |
Keyword(7) |
Sentence-BERT |
Keyword(8) |
focal loss |
1st Author's Name |
Mastuti Puspitasari |
1st Author's Affiliation |
The University of Electro-Communications (UEC) |
2nd Author's Name |
Takuya Takahashi |
2nd Author's Affiliation |
The University of Electro-Communications (UEC) |
3rd Author's Name |
Gen Hori |
3rd Author's Affiliation |
Asia University (AU) |
4th Author's Name |
Shigeki Sagayama |
4th Author's Affiliation |
The University of Electro-Communications (UEC) |
5th Author's Name |
Toru Nakashika |
5th Author's Affiliation |
The University of Electro-Communications (UEC) |
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Speaker |
Author-1 |
Date Time |
2023-06-24 13:50:00 |
Presentation Time |
140 minutes |
Registration for |
SP |
Paper # |
SP2023-18 |
Volume (vol) |
vol.123 |
Number (no) |
no.88 |
Page |
pp.86-90 |
#Pages |
5 |
Date of Issue |
2023-06-16 (SP) |