Lyric Jumper: A Lyrics-Based Music Exploratory Web Service by Modeling Lyrics Generative Process
Lyric Jumper: A Lyrics-Based Music Exploratory Web Service by Modeling Lyrics Generative Process
复制标题
Lyric Jumper：通过对歌词生成过程进行建模来提供基于歌词的音乐探索 Web 服务
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Masataka Goto
中科院分区：
文献类型：
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作者：
Kosetsu Tsukuda;Keisuke Ishida;Masataka Goto
每个艺术家都有自己的口味的主题的歌词，如“爱”和“友谊。”考虑到艺术家的品味，音乐信息检索带来了新的应用：选择艺术家的基础上的主题的歌词，并找到陌生的艺术家谁有相似的品味，最喜欢的艺术家。虽然先前的研究应用潜在狄利克雷分配（LDA）的歌词分析主题，LDA是无法捕捉艺术家的口味。在本文中，我们提出了一个主题模型，可以处理艺术家的主题的歌词。我们的模型假设每个艺术家都有一个主题分布，并根据该分布为每首歌曲分配一个主题。我们使用真实世界数据集的实验结果表明，我们的模型优于LDA的困惑。通过应用我们的模型来估计3,722位艺术家的147,990首歌词的主题，我们实现了一个名为Lyric Jumper的Web服务，使用户能够根据估计的主题探索歌词。Lyric Jumper提供了艺术家主题品味可视化和基于主题相似度的艺术家推荐等功能。我们还分析了Lyric Jumper上12，353名用户的操作日志，并展示了Lyric Jumper的实用性，特别是在推荐歌词中与主题相关的短语方面。
Each artist has their own taste for topics of lyrics such as “love” and “friendship.” Considering such artist’s taste brings new applications in music information retrieval: choosing an artist based on topics of lyrics and finding unfamiliar artists who have similar taste to a favorite artist. Although previous studies applied latent Dirichlet allocation (LDA) to lyrics to analyze topics, LDA was not able to capture the artist’s taste. In this paper, we propose a topic model that can deal with the artist’s taste for topics of lyrics. Our model assumes each artist has a topic distribution and a topic is assigned to each song according to the distribution. Our experimental results using a realworld dataset show that our model outperforms LDA in terms of the perplexity. By applying our model to estimate topics of 147,990 lyrics by 3,722 artists, we implement a web service called Lyric Jumper that enables users to explore lyrics based on the estimated topics. Lyric Jumper provides functions such as artist’s topic taste visualization and topic-similarity-based artist recommendation. We also analyze operation logs obtained from 12,353 users on Lyric Jumper and show the usefulness of Lyric Jumper especially in recommending topic-related phrases in lyrics.
DOI：
10.1073/pnas.0307752101
发表时间：
2004-04-06
影响因子：
11.1
作者：
Griffiths, TL;Steyvers, M
通讯作者：
Steyvers, M
通过新颖的注意力模块实现自然情感语音转换
DOI：
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发表时间：
2022
期刊：
影响因子：
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作者：
陳 訓泉;陳 金輝;高島 遼一;滝口 哲也
通讯作者：
滝口 哲也