Automatic genre classification of music content: a survey
N Scaringella, G Zoia, D Mlynek - IEEE Signal Processing …, 2006 - ieeexplore.ieee.org
This paper reviews the state-of-the-art in automatic genre classification of music collections
through three main paradigms: expert systems, unsupervised classification, and supervised …
through three main paradigms: expert systems, unsupervised classification, and supervised …
Content-based music information retrieval (cb-mir) and its applications toward the music industry: A review
A huge increase in the number of digital music tracks has created the necessity to develop
an automated tool to extract the useful information from these tracks. As this information has …
an automated tool to extract the useful information from these tracks. As this information has …
Features for content-based audio retrieval
Today, a large number of audio features exists in audio retrieval for different purposes, such
as automatic speech recognition, music information retrieval, audio segmentation, and …
as automatic speech recognition, music information retrieval, audio segmentation, and …
Aggregate features and ADABOOST for music classification
We present an algorithm that predicts musical genre and artist from an audio waveform. Our
method uses the ensemble learner A DA B OOST to select from a set of audio features that …
method uses the ensemble learner A DA B OOST to select from a set of audio features that …
Classification accuracy is not enough: On the evaluation of music genre recognition systems
BL Sturm - Journal of Intelligent Information Systems, 2013 - Springer
We argue that an evaluation of system behavior at the level of the music is required to
usefully address the fundamental problems of music genre recognition (MGR), and indeed …
usefully address the fundamental problems of music genre recognition (MGR), and indeed …
A survey of evaluation in music genre recognition
BL Sturm - International Workshop on Adaptive Multimedia …, 2012 - Springer
Much work is focused upon music genre recognition (MGR) from audio recordings, symbolic
data, and other modalities. While reviews have been written of some of this work before, no …
data, and other modalities. While reviews have been written of some of this work before, no …
[PDF][PDF] Automatic musical pattern feature extraction using convolutional neural network
Music genre classification has been a challenging yet promising task in the field of music
information retrieval (MIR). Due to the highly elusive characteristics of audio musical data …
information retrieval (MIR). Due to the highly elusive characteristics of audio musical data …
Temporal feature integration for music genre classification
Temporal feature integration is the process of combining all the feature vectors in a time
window into a single feature vector in order to capture the relevant temporal information in …
window into a single feature vector in order to capture the relevant temporal information in …
[KNIHA][B] Music data mining
During the last 10 years there has been a dramatic shift in how music is produced,
distributed, and consumed. A combination of advances in digital storage, audio …
distributed, and consumed. A combination of advances in digital storage, audio …
A machine learning approach to automatic music genre classification
This paper presents a non-conventional approach for the automatic music genre
classification problem. The proposed approach uses multiple feature vectors and a pattern …
classification problem. The proposed approach uses multiple feature vectors and a pattern …