One Comment from One Perspective : An Effective Strategy for Enhancing Automatic Music Comment

Tengfei Huo, Zhiqiang Liu, Jinchao Zhang, Jie Zhou


Abstract
The automatic generation of music comments is of great significance for increasing the popularity of music and the music platform’s activity. In human music comments, there exists high distinction and diverse perspectives for the same song. In other words, for a song, different comments stem from different musical perspectives. However, to date, this characteristic has not been considered well in research on automatic comment generation. The existing methods tend to generate common and meaningless comments. In this paper, we propose an effective multi-perspective strategy to enhance the diversity of the generated comments. The experiment results on two music comment datasets show that our proposed model can effectively generate a series of diverse music comments based on different perspectives, which outperforms state-of-the-art baselines by a substantial margin.
Anthology ID:
2020.coling-main.259
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
2889–2899
Language:
URL:
https://aclanthology.org/2020.coling-main.259
DOI:
10.18653/v1/2020.coling-main.259
Bibkey:
Cite (ACL):
Tengfei Huo, Zhiqiang Liu, Jinchao Zhang, and Jie Zhou. 2020. One Comment from One Perspective : An Effective Strategy for Enhancing Automatic Music Comment. In Proceedings of the 28th International Conference on Computational Linguistics, pages 2889–2899, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
One Comment from One Perspective : An Effective Strategy for Enhancing Automatic Music Comment (Huo et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.259.pdf
Code
 htfhxx/commentperspective
Terminologies: