- 學位論文
從音訊到主題：用卷積神經網路學習語意
From Audio to Topics: Learning Semantics with Convolutional Neural Network
並列摘要
Nowadays, music has become an import part of our lives. As cloud-based streaming service becomes popular, people are more dependent on music. Music as a tool of expressing emotions, it is rich in semantics. In previous genre and mood classification tasks, some people already show that combining lyrics and audio features can improve the results. Their research indicates there are potential relationship between audio and lyrics. Lyrics directly describe a song’s topic, while audio can expand the emotions. Nevertheless, lyrics can be incomplete or missing. If we can learn the topics from audio, we can guess the possible topics for a song without using lyrics. We proposed an unsupervised two-stage method. First, we learn the latent topics in lyrics by topic model. Second, we transfer audio signal to topic distribution via a convolutional neural network. We show that this framework can indeed learns a semantical representation from audio and can be directly applied to song retrievals. We can not only search the songs with lyrics. For those songs without lyrics, i.e. classical songs, we can also provide a reasonable result.
參考文獻
延伸閱讀
- 趙偉成（2019）。探討預訓練神經網路於語音內涵之機器閱讀理解〔碩士論文，國立臺灣師範大學〕。華藝線上圖書館。https://doi.org/10.6345/NTNU201900461
- 周伯威（2015）。以深層與卷積類神經網路建構聲學模型之大字彙連續語音辨識〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2015.00754
- 黃臆榤（2018）。結合語意關鍵詞與卷積神經網路之文本分類研究〔碩士論文，國立清華大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0016-1803201914463303
- 蔡旻諺、徐禾瀚、卓信宏（2020）。Low-Rate Denial-of-Service detection based on Convolutional Neural Network。資訊安全通訊，26(3)，51-62。https://www.airitilibrary.com/Article/Detail?DocID=a0000270-202008-202009170014-202009170014-51-62
- Kang, H. P. (2013). Improving Convolutional Neural Networks by Separable Filters [master's thesis, National Tsing Hua University]. Airiti Library. https://doi.org/10.6843/NTHU.2013.00814