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Multimodal music information processing and retrieval: survey and future challenges
[article]
2019
arXiv
pre-print
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2019
2019 International Workshop on Multilayer Music Representation and Processing (MMRP)
unpublished
doi:10.1109/mmrp.2019.00012 fatcat:4zvm6fvm7jdtjgcrtcxmxeibfi
doi:10.1109/mmrp.2019.00012 fatcat:4zvm6fvm7jdtjgcrtcxmxeibfi
Subsequently, we analyze existing information fusion approaches, and we conclude with the set of challenges that Music Information Retrieval and Sound and Music Computing research communities should focus ...
This paper critically reviews the various approaches adopted in Music Information Processing and Retrieval and highlights how multimodal algorithms can help Music Computing applications. ...
Other multimodal classification tasks found in the literature are: • artist identification, through lyrics and audio fusion [38] ; • derivative works classification of youtube video through audio, video ...
arXiv:1902.05347v1
fatcat:i2indkxk3vcmxajn6ajkh56wva
An Evaluation of Symbolic Feature Sets and Their Combination for Music Genre Classification
2013
2013 IEEE International Conference on Systems, Man, and Cybernetics
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In this paper we use two different symbolic feature sets for genre classification and combine them using an early fusion approach. ...
The automatic music genre classification task is an active area of research in the field of Music Information Retrieval. ...
This is to avoid that instead of performing automatic music genre classification the system will learn to perform automatic artist identification. ...
doi:10.1109/smc.2013.327
dblp:conf/smc/PiccoliSLP13
fatcat:wk2qttqalndqtmtrbpcw3svrva
A professionally annotated and enriched multimodal data set on popular music
2013
Proceedings of the 4th ACM Multimedia Systems Conference on - MMSys '13
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Different sets of annotations as well as music context data -collaboratively generated user tags, web pages about artists and albums, and the annotation labels provided by music experts -are included too ...
This paper presents the MusiClef data set, a multimodal data set of professionally annotated music. ...
MIREX covers various Music-IR tasks proposed by the community, ranging from "Audio Music Similarity and Retrieval" to "Audio Tag Affinity Estimation" and from "Classical Composer Identification" to "Genre ...
doi:10.1145/2483977.2483985
dblp:conf/mmsys/SchedlOLP13
fatcat:ho4xrkrkhvhvbjumpk7vujywke
Multimodal Deep Learning for Music Genre Classification
2018
Transactions of the International Society for Music Information Retrieval
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In this work, an approach to learn and combine multimodal data representations for music genre classification is proposed. ...
Music genre labels are useful to organize songs, albums, and artists into broader groups that share similar musical characteristics. ...
Acknowledgements This work was partially funded by the Spanish Ministry of Economy and Competitiveness under the Maria de Maeztu Units of Excellence Programme (MDM-2015-0502). ...
doi:10.5334/tismir.10
fatcat:xfkr3e3atne3hbiwoyaxqv35za
A Multimodal End-To-End Deep Learning Architecture for Music Popularity Prediction
2020
IEEE Access
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In addition, an innovative multimodal end-to-end Deep Learning architecture named as HitMusicNet is presented for predicting popularity in music recordings. ...
Thus, innovative methods for retrieving specific information from large volumes of data related with music arises as a potential challenge within the Music Information Retrieval (MIR) framework. ...
Firstly, a multimodal updated database has been built as a fusion of two main platforms: Spotify and Genius, containing more than 100K tracks collected from 26 different countries, with the purpose of ...
doi:10.1109/access.2020.2976033
fatcat:cm4gvs373vg5jlj6ouwuege54y
Musiclef: A Benchmark Activity In Multimodal Music Information Retrieval
2011
Zenodo
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fusion techniques. ...
Although systems for automatic music identification already give good results, the combination of segmentation and identification of continuous recordings is not well investigated yet. ...
focus on multimodal approaches. ...
doi:10.5281/zenodo.1416505
fatcat:da4tniue3nbuzfwyv2vrh7rfee
Automatic Music Genre Classification of Audio Signals with Machine Learning Approaches
2013
GSTF International Journal on Computing
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The increase of the music databases on the personal collection and the Internet has brought a great demand for music information retrieval, and especially automatic musical genre classification. ...
The final genre classification is obtained from the set of individual results according to a weighting combination late fusion method and it outperformed the trained fusion method. ...
Music is an inherently multimodal type of data and Mayer et al. proposed an approach for multi-modal classification of music using classifier ensemble techniques [8] . ...
doi:10.7603/s40601-013-0014-0
fatcat:x4g4qj53mjdw5gg3jyg2wkpx5m
Automatic Music Genre Classification of Audio Signals with Machine Learning Approaches
2013
GSTF International Journal on Computing
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The increase of the music databases on the personal collection and the Internet has brought a great demand for music information retrieval, and especially automatic musical genre classification. ...
The final genre classification is obtained from the set of individual results according to a weighting combination late fusion method and it outperformed the trained fusion method. ...
Music is an inherently multimodal type of data and Mayer et al. proposed an approach for multi-modal classification of music using classifier ensemble techniques [8] . ...
doi:10.5176/2251-3043_3.2.251
fatcat:b4rf2324qbg5vlzb2sbgjwjxce
Knowledge Extraction And Representation Learning For Music Recommendation And Classification
2017
Zenodo
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In this thesis, we address the problems of classifying and recommending music present in large collections. ...
We focus on the semantic enrichment of descriptions associated to musical items (e.g., artists biographies, album reviews, metadata), and the exploitation of multimodal data (e.g., text, audio, images) ...
Multimodal fusion There are several approaches in the literature for multimodal feature learning (Ngiam et al., 2011; Srivastava & Salakhutdinov, 2012) , and late fusion of multimodal feature vectors ...
doi:10.5281/zenodo.1048497
fatcat:kdh5jhvocbh3riwln6n2f756su
Knowledge Extraction And Representation Learning For Music Recommendation And Classification
2017
Zenodo
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In this thesis, we address the problems of classifying and recommending music present in large collections. ...
We focus on the semantic enrichment of descriptions associated to musical items (e.g., artists biographies, album reviews, metadata), and the exploitation of multimodal data (e.g., text, audio, images) ...
Multimodal fusion There are several approaches in the literature for multimodal feature learning (Ngiam et al., 2011; Srivastava & Salakhutdinov, 2012) , and late fusion of multimodal feature vectors ...
doi:10.5281/zenodo.1100973
fatcat:yfpmc6qxbbakjp6qzvywyoaoci
Multi-Modal Music Information Retrieval: Augmenting Audio-Analysis with Visual Computing for Improved Music Video Analysis
[article]
2020
arXiv
pre-print
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The experiments are conducted for three MIR tasks Artist Identification, Music Genre Classification and Cross-Genre Classification. ...
In a further consequence it can be concluded that this visual information is music related and thus should be beneficial for the corresponding MIR tasks such as music genre classification or mood recognition ...
Artist Identification: Artist recognition is an important task for music indexing, browsing and retrieval. ...
arXiv:2002.00251v1
fatcat:6cz6rivc3fbg7fahdsnokxfrk4
DEAP: A Database for Emotion Analysis ;Using Physiological Signals
2012
IEEE Transactions on Affective Computing
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We present a multimodal data set for the analysis of human affective states. ...
The electroencephalogram (EEG) and peripheral physiological signals of 32 participants were recorded as each watched 40 one-minute long excerpts of music videos. ...
the number of modalities considered for fusion, m is the classifier for the mth modality, and P i ðXj m Þ is its output for the ith class. ...
doi:10.1109/t-affc.2011.15
fatcat:p4elxka43bhctgwuv56r2j4eei
Music Interpretation Analysis. A Multimodal Approach To Score-Informed Resynthesis of Piano Recordings
[article]
2022
arXiv
pre-print
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For this, a novel conceptual and mathematical framework named "Music Interpretation Analysis" (MIA) is presented. ...
Second, the Thesis describes further works aiming at the democratization of music production tools via automatic resynthesis: 1) it elaborates software and file formats for historical music archiving and ...
Acknowledgments 1,2 Not many thanks should be given for this work. ...
arXiv:2205.00941v1
fatcat:nnbfvywdyjgtfcapfq4nn2c3bq
'José María Arguedas is My John Lennon': Arguedas as Cultural Hero in Lima's Independent Music Scene
2018
Iberoamericana: Nordic Journal of Latin American and Caribbean Studies
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In addition to interviews, my material for this article includes song lyrics and music videos of their two songs featured on the 'Mana Wanaq' album, and use supporting information about the artists from ...
the recycling of the past through both artistic and musical forms ' (2018: 114) . ...
Her dissertation is entitled "Indigenismo for the digital age: Mestizaje, cultural capital, and fusion aesthetics in Lima's independent music scene". ...
doi:10.16993/iberoamericana.424
fatcat:khvrtp3iyzfzfg5ehmeviqpi7a
Report on WEMIS 2009
2009
D-Lib Magazine
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WEMIS 2009% ii this end, music content should thus include the symbolic representation of music works and the information on the structure of music pieces. ...
We would like to express our sincere gratitude to the ECDL' 09 organizers, and specially to the members of the program committee for ensuring a high quality proceedings. This document can be found at: ...
We present the results of an online experiment where alternative approaches for matching POIs and music, based on tagging and text matching, have been tested with users.
ACKNOWLEDGEMENTS ...
doi:10.1045/november2009-orio
fatcat:zel4p7ushfhc7edqcafbryjlvu
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