Is it possible use algorithms to find trends in the history of popular music? And is it possible to predict the characteristics of future music genres? In order to answer these questions, we produced a hand-crafted dataset with the intent to put together features about style, psychology, sociology and typology, annotated by music genre and indexed by time and decade. We collected a list of popular genres by decade from Wikipedia and scored music genres based on Wikipedia descriptions. Using statistical and machine learning techniques, we find trends in the musical preferences and use time series forecasting to evaluate the prediction of future music genres.
The MPB Corpus: A Dataset of Melody, Rhythm, Harmony, and Melody-Harmony Relationships in Brazilian Popular Music
School of Music, Federal University of Rio de Janeiro（里约热内卢联邦大学音乐学院）；Institute of Mathematics, Federal University of Rio de Janeiro（里约热内卢联邦大学数学研究所）；Institut für Theorie und Geschichte, Anton Bruckner Universität（安东布鲁克纳大学理论与历史研究所）
Indian Institute of Technology Kanpur（印度理工学院坎普尔分校）
Music Genres, as a popular meta-data of music, are very useful to organize, explore or search music datasets. Soft music genres are weighted multiple-genre annotations to songs. In this initial work, we propose horizontally stacked bar charts to represent a music dataset annotated by these soft music genres. For this purpose, we take an example of a toy dataset consisting of songs labelled with help of three music genres; Blues, Jazz and Country. We demonstrate how such a stacked bar chart can be used as a slider for user-input in an interface. We implement this by embedding this genre bar in …
The Swiss AI Lab, IDSIA, USI & SUPSI（瑞士人工智能实验室，IDSIA，卢加诺大学与瑞士南部应用科学与艺术大学）；Institute of Neuroinformatics, ETH Zurich（苏黎世联邦理工学院神经信息学研究所）；AI Initiative, KAUST（阿卜杜拉国王科技大学人工智能计划）
Ping An Technology（平安科技）；New York University（纽约大学）
We proposed a model for the Conference of Music and Technology (CSMT2020) data challenge of melody classification. Our model used the Performance Event Vector as the input sequence to build a Bidirectional RNN network for classfication. The model achieved a satisfying performance on the development dataset and Wikifonia dataset. We also discussed the effect of several hyper-parameters, and created multiple prediction outputs for the evaluation dataset.
Wikipedia is the largest online encyclopedia, used by algorithms and web users as a central hub of reliable information on the web. The quality and reliability of Wikipedia content is maintained by a community of volunteer editors. Machine learning and information retrieval algorithms could help scale up editors' manual efforts around Wikipedia content reliability. However, there is a lack of large-scale data to support the development of such research. To fill this gap, in this paper, we propose Wiki-Reliability, the first dataset of English Wikipedia articles annotated with a wide set of con…
Max Planck Institute for Human Cognitive and Brain Sciences（马克斯·普朗克人类认知与脑科学研究所）；Max Planck Institute for Empirical Aesthetics（马克斯·普朗克经验美学研究所）；Leipzig University（莱比锡大学）；New York University Abu Dhabi（纽约大学阿布扎比分校）
Do people from different cultural backgrounds perceive the mood in music the same way? How closely do human ratings across different cultures approximate automatic mood detection algorithms that are often trained on corpora of predominantly Western popular music? Analyzing 166 participants responses from Brazil, South Korea, and the US, we examined the similarity between the ratings of nine categories of perceived moods in music and estimated their alignment with four popular mood detection algorithms. We created a dataset of 360 recent pop songs drawn from major music charts of the countries …
Google Research（谷歌研究院）；University of Maryland（马里兰大学）
We release FoolMeTwice (FM2 for short), a large dataset of challenging entailment pairs collected through a fun multi-player game. Gamification encourages adversarial examples, drastically lowering the number of examples that can be solved using "shortcuts" compared to other popular entailment datasets. Players are presented with two tasks. The first task asks the player to write a plausible claim based on the evidence from a Wikipedia page. The second one shows two plausible claims written by other players, one of which is false, and the goal is to identify it before the time runs out. Player…
Complex Knowledge Base Question Answering is a popular area of research in the past decade. Recent public datasets have led to encouraging results in this field, but are mostly limited to English and only involve a small number of question types and relations, hindering research in more realistic settings and in languages other than English. In addition, few state-of-the-art KBQA models are trained on Wikidata, one of the most popular real-world knowledge bases. We propose CLC-QuAD, the first large scale complex Chinese semantic parsing dataset over Wikidata to address these challenges. Togeth…
