Deep learning for audio-based music classification and tagging: Teaching computers to distinguish rock from bach
Over the last decade, music-streaming services have grown dramatically. Pandora, one
company in the field, has pioneered and popularized streaming music by successfully …
company in the field, has pioneered and popularized streaming music by successfully …
[PDF][PDF] Hit Song Prediction: Leveraging Low-and High-Level Audio Features.
E Zangerle, M Vötter, R Huber, YH Yang - ISMIR, 2019 - evazangerle.at
Assessing the potential success of a given song based on its acoustic characteristics is an
important task in the music industry. This task has mostly been approached from an internal …
important task in the music industry. This task has mostly been approached from an internal …
Music popularity: Metrics, characteristics, and audio-based prediction
Understanding music popularity is important not only for the artists who create and perform
music but also for the music-related industry. It has not been studied well how music …
music but also for the music-related industry. It has not been studied well how music …
Novel datasets for evaluating song popularity prediction tasks
Estimating the success of a song before its release is an important music industry task.
Current work uses audio descriptors to predict the success (popularity) of a song, where …
Current work uses audio descriptors to predict the success (popularity) of a song, where …
Pairwise learning to rank for hit song prediction
Predicting the popularity of songs in advance is of great interest to the music industry, with
possible applications including assessing the potential of a new song, automated …
possible applications including assessing the potential of a new song, automated …
Neural loop combiner: Neural network models for assessing the compatibility of loops
Music producers who use loops may have access to thousands in loop libraries, but finding
ones that are compatible is a time-consuming process; we hope to reduce this burden with …
ones that are compatible is a time-consuming process; we hope to reduce this burden with …
HSP datasets: Insights on song popularity prediction
Estimating the success of a song before its release is an important music industry task. This
work uses audio descriptors to predict the success (popularity) of a song, where typical …
work uses audio descriptors to predict the success (popularity) of a song, where typical …
[PDF][PDF] Hitpredict: Predicting hit songs using spotify data
E Georgieva, M Suta, N Burton - STANFORD COMPUTER SCIENCE …, 2018 - academia.edu
In the current study, we approached the Hit Song Science problem, aiming to predict which
songs will become Billboard Hot 100 hits. We collated a dataset of approximately 4,000 hit …
songs will become Billboard Hot 100 hits. We collated a dataset of approximately 4,000 hit …
Context-aware network analysis of music streaming services for popularity estimation of artists
Y Matsumoto, R Harakawa, T Ogawa… - IEEE Access, 2020 - ieeexplore.ieee.org
A novel trial for estimating popularity of artists in music streaming services (MSS) is
presented in this paper. The main contribution of this paper is to improve extensibility for …
presented in this paper. The main contribution of this paper is to improve extensibility for …
Music Era Recognition Using Supervised Contrastive Learning and Artist Information
Does popular music from the 60s sound different than that of the 90s? Prior study has shown
that there would exist some variations of patterns and regularities related to instrumentation …
that there would exist some variations of patterns and regularities related to instrumentation …