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Music genre classification using explicit semantic analysis

Kamelia Aryafar, Ali Shokoufandeh
2011 Proceedings of the 1st international ACM workshop on Music information retrieval with user-centered and multimodal strategies - MIRUM '11  
Recent work has proposed the use of an automated method based on explicit semantic analysis to identify the most representative genre patterns in a large data set.  ...  The method only uses signal-based mel frequency cepstral coefficients (MFCCs) as audio feature representation and improves upon previous methods that use the same set of features for music genre classification  ...  Experiment: Music genre classification In our experiments, we use the publicly available benchmark dataset for audio classification and clustering proposed by Homburg et al.  ... 
doi:10.1145/2072529.2072539 dblp:conf/mm/AryafarS11 fatcat:xlaf7dx4wjdffkbi5j4ah5eit4

The MX Formalism for Semantic Web Compatible Representation of Music Metadata [chapter]

S. Castano, A. Ferrara, G. Haus, L. A. Ludovico, S. Montanelli, G. Racca, G. Vercellesi
2005 Lecture Notes in Computer Science  
and semantic features, by means of XML and OWL.  ...  In this paper, we present the MX formalism that aims to address this limitation of the existing formats, by providing a Semantic Web compatible representation of music information in terms of structural  ...  Semantic retrieval of music resources The MX semantic layer can be used to improve music pieces retrieval from the traditional keyword-based approach to a semantics-based approach.  ... 
doi:10.1007/11551898_9 fatcat:lkdtq6ktqra4ffiu5qblu34bkq

Faceted Ontological Representation for a Music Domain

Devika P. Madalli, B. Preedip Balaji, and Amit Kumar Sarangi
2015 Knowledge organization  
She is on the advisory board of Universal Decimal Classification and a co-chair of the interest group on Agricultural Data at the Research Data Alliance.  ...  His research interests lie in the semantic web, digital libraries and knowledge organization.  ...  YouTube and Allmusic.com use genres for browsing music videos and to navigate musical content on their websites (see: http://www.youtube.com/music; http://www.allmusic.com/genres).  ... 
doi:10.5771/0943-7444-2015-1-9 fatcat:dtso3hipojaljcrtnv52jmvrna

Music Genres Classification using Text Categorization Method

Kai Chen, Sheng Gao, Yongwei Zhu, Qibin Sun
2006 2006 IEEE Workshop on Multimedia Signal Processing  
We use latent semantic indexing (LSI) technique that is widely adopted in text categorization for music genre classification.  ...  In this paper, we propose a new framework using text category methods to classify music genres. This framework is different from current methods for Music genre classification.  ...  Each piece of music can be considered as a text-like semantic music document and latent semantic indexing is adopted for music genre classification.  ... 
doi:10.1109/mmsp.2006.285301 dblp:conf/mmsp/ChenGZS06 fatcat:ao6rutv3zbh3fpb246yl3fx25i

A content-based system for music recommendation and visualization of user preferences working on semantic notions

Dmitry Bogdanov, Martin Haro, Ferdinand Fuhrmann
2011 2011 9th International Workshop on Content-Based Multimedia Indexing (CBMI)  
For the audio analysis we used the capabilities of the Canoris API.  ...  Thereafter, the system generates music recommendations, using a semantic music similarity measure, and a user's preference visualization, mapping semantic descriptors to visual elements.  ...  For each uploaded audio file a wide set of analysis features can be retrieved, ranging from frame-based low-level features (such as MFCCs) up to semantic descriptions (such as mood or genre labels) of  ... 
doi:10.1109/cbmi.2011.5972554 dblp:conf/cbmi/BogdanovHFXGH11 fatcat:qyardjwo2jcxhf5ddov44ifo4u

Representing Musical Genre: A State of the Art

Jean-Julien Aucouturier, Fran�ois Pachet
2003 Journal of New Music Research  
Musical genre is probably the most popular music descriptor.  ...  In the context of large musical databases and Electronic Music Distribution, genre is therefore a crucial metadata for the description of music content.  ...  Acknowledgement This work has been founded by the European IST project CUIDADO (Content-based Unified Interfaces and Descriptors for Audio/music Databases available On-line).  ... 
doi:10.1076/jnmr.32.1.83.16801 fatcat:sefhdkgnxzeelifm6aws6oaop4

Video classification using spatial-temporal features and PCA

Li-Qun Xu, Yongmin Li
2003 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698)  
Five popular TV broadcast genre are studied including sports, cartoon, news, commercial and music.  ...  Second, the feature vector is further processed using Principal Component Analysis to reduce the spatial-temporal redundancy while exploiting the correlations between feature elements, which give rise  ...  Classification results on individual genres Finally, to demonstrate the inter-dependence among semantic contents belonging to these five video genres, we compute the confusion matrix of the classification  ... 
doi:10.1109/icme.2003.1221354 dblp:conf/icmcs/XuL03 fatcat:segktfaydngoxlc2jgzvuum6ry

Lyric document embeddings for music tagging [article]

Matt McVicar, Bruno Di Giorgi, Baris Dundar, Matthias Mauch
2021 arXiv   pre-print
Evaluating on a wide range of tagging tasks such as genre classification, explicit content identification and era detection, we find that averaging word embeddings outperform more complex architectures  ...  We present an empirical study on embedding the lyrics of a song into a fixed-dimensional feature for the purpose of music tagging.  ...  - fully been applied to explicit song detection [20], genre classification [10] and music recommendation [27].  ... 
arXiv:2112.11436v1 fatcat:wdogpm6rprdvpaxp2sw7potppq

Formalizing The Problem Of Music Description

Bob L. Sturm, Rolf Bardeli, Thibault Langlois, Valentin Emiya
2014 Zenodo  
An analysis of an RMDS depends on an explicit use case. The definition of the use case in Dannenberg et al.  ...  an RMDS uses all of RΩ classification accuracy of RT GS The system analysis performed by Dannenberg et al. involve experiments measuring the mean accuracy of all sys-15th International Society for Music  ... 
doi:10.5281/zenodo.1414914 fatcat:wlameqdg6fbw5bhcmj42txyehy

Mining metadata from the web for AcousticBrainz

Alastair Porter, Dmitry Bogdanov, Xavier Serra
2016 Proceedings of the 3rd International workshop on Digital Libraries for Musicology - DLfM 2016  
These tools expand on data present in the AcousticBrainz database, which contains software-generated analysis of music audio files.  ...  Semantic annotations of music collections in digital libraries are important for organization and navigation of the collection.  ...  For example, many datasets commonly used in genre classification contain no more than 10 genre labels [8] . It is also common for datasets to contain annotations covering only popular music.  ... 
doi:10.1145/2970044.2970048 dblp:conf/dlfm/PorterBS16 fatcat:7alut3tkgvbclfvyxjqqmroj3q

Knowledge based Semantic Annotation Generation of Music

Sunitha Abburu
2012 International Journal of Computer Applications  
The generated semantic annotations can be used in semantic indexing and retrieval, which will enhance the performance of the retrieval system. General Terms Semantic Information Retrieval.  ...  The current research designs and implements a tool M-SAGT -Music Semantic Annotation Generation Tool.  ...  Music genre is widely used to classify music and to aid in retrieval and discovery. However there is no general agreement as to the correct genre taxonomy.  ... 
doi:10.5120/7206-9990 fatcat:l52l55iywrbwtnpvdnaoevcbxu

Zero-shot Learning for Audio-based Music Classification and Tagging [article]

Jeong Choi, Jongpil Lee, Jiyoung Park, Juhan Nam
2020 arXiv   pre-print
This intrinsically cannot handle unseen labels such as newly added music genres or semantic words that users arbitrarily choose for music retrieval.  ...  The other is using general word semantic information based on Million Song Dataset and Last.fm tag annotations.  ...  These examples may be equivalent to music genre classification where corresponding attributes are musical instruments.  ... 
arXiv:1907.02670v2 fatcat:hwuhvu77qfbvfg2gob3zzdpthm

Zero-shot Learning for Audio-based Music Classification and Tagging

Jeong Choi, Jongpil Lee, Jiyoung Park, Juhan Nam
2019 Zenodo  
This intrinsically cannot handle unseen labels such as newly added music genres or semantic words that users arbitrarily choose for music retrieval.  ...  The other is using general word semantic information based on Million Song Dataset and Last.fm tag annotations.  ...  These examples may be equivalent to music genre classification where corresponding attributes are musical instruments.  ... 
doi:10.5281/zenodo.3527740 fatcat:cmg3wecddvextbc5cepmwnu7p4

Love Me, Love Me, Say (and Write!) that You Love Me: Enriching the WASABI Song Corpus with Lyrics Annotations [article]

Michael Fell, Elena Cabrio, Elmahdi Korfed, Michel Buffa, Fabien Gandon
2020 arXiv   pre-print
We present the WASABI Song Corpus, a large corpus of songs enriched with metadata extracted from music databases on the Web, and resulting from the processing of song lyrics and from audio analysis.  ...  as their structure segmentation, their topics, the explicitness of the lyrics content, the salient passages of a song and the emotions conveyed.  ...  For emotion classification, they use bags of words and concepts, as musical features key and notes.  ... 
arXiv:1912.02477v2 fatcat:eltjjg2kjbcynkdtutgmfgyw2u

Using Artist Similarity To Propagate Semantic Information

Joon Hee Kim, Brian Tomasik, Douglas Turnbull
2009 Zenodo  
INTRODUCTION Tags, such as "hair metal", "afro-cuban influences", and "grrl power", are semantic labels that are useful for semantic music information retrieval (IR).  ...  This suggests that collaborative filtering is useful for determining semantic similarity as well as music recommendation.  ... 
doi:10.5281/zenodo.1416509 fatcat:3ugls7gkercrfgtibhdzioswm4
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