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Annotating Music Collections: How Content-Based Similarity Helps To Propagate Labels

Mohamed Sordo, Cyril Laurier, Òscar Celma
2007 Zenodo  
ACKNOWLEDGEMENTS This research has been partially supported by the e-Content plus project VARIAZIONI 4 . We are also very grateful for  ...  CONCLUSIONS AND FUTURE WORK Our objective was to test how the content-based similarity can propagate labels.  ...  Thus, the main goal of our work is to ease the process of annotating music collections, by using content-based similarity distance as a way to propagate labels among songs.  ... 
doi:10.5281/zenodo.1415708 fatcat:szjyzfe4vbhxdihx3pqqjqldge

Semi-Automatic Annotation of Music Collections

Mohaed Sordo, Xavier Serra
2007 Zenodo  
The Thesis presents two experiments followed for the evaluation of the annotation process the first experiment consists on testing how the contentbased similarity can propagate labels.  ...  contentbased similarity.  ...  With respect to the first experiment, the objective was to test how the content-based similarity can propagate labels.  ... 
doi:10.5281/zenodo.3743141 fatcat:5bmjq5ccr5euxhltdxrzpjfwky

Collecting Ground Truth Annotations For Drum Detection In Polyphonic Music

Koen Tanghe, Micheline Lesaffre, Sven Degroeve, Marc Leman, Bernard De Baets, Jean-Pierre Martens
2005 Zenodo  
The authors wish to thank Liesbeth De Voogdt and Dirk Van Steelant for their help with the annotator guidelines, music selection and practical organization.  ...  ACKNOWLEDGEMENTS This work was done in the context of the "Musical Audio Mining" (MAMI) project, which is funded by the Flemish Institute for the Promotion of Scientific and Technological Research in Industry  ...  In the same way that melody lines can be seen as a representation of one aspect of the musical content of a piece of music, drum sequences can be seen as another type of musical content representation,  ... 
doi:10.5281/zenodo.1417714 fatcat:jwiohalnuze7ncslo5jj6dqbui

Mucosa: A Music Content Semantic Annotator

Perfecto Herrera, Òscar Celma, Jordi Massaguer, Pedro Cano, Emilia Gómez, Fabien Gouyon, Markus Koppenberger
2005 Zenodo  
ACKNOWLEDGMENTS The research and development reported here was partially funded by the EU-FP6-IST-507142 project SIMAC (Semantic Interaction with Music Audio Contents) project.  ...  The authors would like to thank Edgar Barroso, and the Audioclas and CLAM teams for their support to the project.  ...  A "propagate" button makes possible the propagation of the label to other similar songs, or to other similar artists' songs.  ... 
doi:10.5281/zenodo.1415980 fatcat:2gywtu6xuffgpjr53syhosnjtq

Annotator subjectivity in harmony annotations of popular music

Hendrik Vincent Koops, W. Bas de Haas, John Ashley Burgoyne, Jeroen Bransen, Anna Kent-Muller, Anja Volk
2019 Journal of New Music Research  
This suggests that current ACE algorithms are powerful enough to tune themselves to particular annotators' idiosyncrasies.  ...  In this paper, we introduce and analyse the Chordify Annotator Subjectivity Dataset (CASD) containing chord labels for 50 songs from 4 expert annotators in order to gain a better understanding of the differences  ...  Acknowledgments The authors would like to thank Matt McVicar, Arthur Flexer, Alan Marsden and anonymous reviewers for their feedback on an earlier draft of this paper.  ... 
doi:10.1080/09298215.2019.1613436 fatcat:uzs2nk3gpfdtjbutzhiqoe5ugi

Enriching music mood annotation by semantic association reasoning

Jun Wang, Xavier Anguera, Xiaoou Chen, Deshun Yang
2010 2010 IEEE International Conference on Multimedia and Expo  
Mood annotation of music is challenging as it concerns not only audio content but also extra-musical information.  ...  Novel ontology-based semantic reasoning methods are applied to effectively bridge content-based information with web-based resources.  ...  RELATED WORK Existing mood annotation research is mainly about how to automatically classify music into mood taxonomy, based on the audio signal itself.  ... 
doi:10.1109/icme.2010.5583243 dblp:conf/icmcs/WangACY10 fatcat:hlcugfm2ure5xp63wj7tk2t6yq

Multilingual music genre embeddings for effective cross-lingual music item annotation

Elena V. Epure, Guillaume Salha, Romain Hennequin
2020 Zenodo  
Recently, in order to explicitly consider this subjectivity, the annotation of music items was modeled as a translation task: predict for a music item its music genres within a target vocabulary or taxonomy  ...  Annotating music items with music genres is crucial for music recommendation and information retrieval, yet challenging given that music genres are subjective concepts.  ...  We crawl a multilingual DBpedia music genre sub-graph and use its words as basis for normalizing new tag systems. We further detail how we assemble the DBpedia-based music genres graph.  ... 
doi:10.5281/zenodo.4245555 fatcat:gp3scv2z4jaqpizov6zrjycbd4

Multilingual Music Genre Embeddings for Effective Cross-Lingual Music Item Annotation [article]

Elena V. Epure and Guillaume Salha and Romain Hennequin
2020 arXiv   pre-print
Recently, in order to explicitly consider this subjectivity, the annotation of music items was modeled as a translation task: predict for a music item its music genres within a target vocabulary or taxonomy  ...  Annotating music items with music genres is crucial for music recommendation and information retrieval, yet challenging given that music genres are subjective concepts.  ...  ACKNOWLEDGEMENTS We would like to thank Manuel Moussallam, Marion Baranes, Anis Khlif and the ISMIR reviewers for their insightful and helpful comments on the paper.  ... 
arXiv:2009.07755v1 fatcat:2ozai2vrtjbofbuxxxx6mzwmeq

You Can Judge an Artist by an Album Cover: Using Images for Music Annotation

Janis Libeks, Douglas Turnbull
2011 IEEE Multimedia  
We also describe a simple computer vision system that can predict music genre tags based on content-based image analysis.  ...  While the perception of music tends to focus on our acoustic listening experience, the image of an artist can play a role in how we categorize (and thus judge) the artistic work.  ...  Our system works by first finding visually similar artists to a given seed artist, and then propagating genre labels from these artists to the seed artist [10] .  ... 
doi:10.1109/mmul.2011.1 fatcat:sjpr4alztjgzrjuu3udhew337a

Temporal Pooling And Multiscale Learning For Automatic Annotation And Ranking Of Music Audio

Philippe Hamel, Simon Lemieux, Yoshua Bengio, Douglas Eck
2011 Zenodo  
The authors would like to thank the Theano developper team.  ...  Many content-based music recommendation systems follow the same recipe with minor variations (see [5] for a review). First, some features are extracted from the audio.  ...  This information is useful for tasks like music recommendation, playlist generation and measuring music similarity.  ... 
doi:10.5281/zenodo.1418236 fatcat:cs2ukhgiene2raylodmn5vvttq

A Constraint-based Approach for Annotating Music Scores with Gestural Information

Daniele P. Radicioni, Vincenzo Lombardo
2007 Constraints  
The highly constrained nature of performers gestures makes this task suitable to be modeled via a constraint-based approach, coupled with a strategy aimed at maximizing the gestural comfort of performers  ...  The physical gestures that operate music instruments are responsible for the qualities of the sound being produced in a performance.  ...  Also, we wish to thank the anonymous referees and the Journal's Editor for their valuable comments and suggestions.  ... 
doi:10.1007/s10601-007-9015-y fatcat:6c36tsqb2vhb7jafblrvkhdury

Weakly supervised collective feature learning from curated media [article]

Yusuke Mukuta, Akisato Kimura, David B Adrian, Zoubin Ghahramani
2018 arXiv   pre-print
During the process of content curation, SNS users collect content items manually from various sources and group them by context, all for their own benefit.  ...  One possible solution to this problem is to employ community contributed text tags as weak labels, however, the concepts underlying a single text tag strongly depends on the users.  ...  that our novel link prediction-based framework is promising. Since our prediction method is simple, more sophisticated methods may provide more discriminative features.  ... 
arXiv:1802.04668v1 fatcat:saa6oaoczbdpbebqbrons7deni

Automatic tagging and geotagging in video collections and communities

Martha Larson, Mohammad Soleymani, Pavel Serdyukov
2011 Proceedings of the 1st ACM International Conference on Multimedia Retrieval - ICMR '11  
Automatically generated tags and geotags hold great promise to improve access to video collections and online communities.  ...  The Tagging Task, Professional involves automatically matching episodes in a collection of Dutch television with subject labels drawn from the keyword thesaurus used by the archive staff.  ...  These annotation forms are similar in that they support users in finding and re-finding video content.  ... 
doi:10.1145/1991996.1992047 dblp:conf/mir/LarsonSS11 fatcat:64ojdcpp3rda3bdt5zfl3knura

A faceted approach to reachability analysis of graph modelled collections

Serwah Sabetghadam, Mihai Lupu, Ralf Bierig, Andreas Rauber
2017 International Journal of Multimedia Information Retrieval  
This leads to various challenges in graph-based information retrieval. This paper is concerned with the reachability analysis of multimodal graph modelled collections.  ...  We obtain 373% recall gain for very hard topics by using our graph model of the collection. Further, by adding semantic links to the collection, we gain a 10% increase in the overall recall.  ...  the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  ... 
doi:10.1007/s13735-017-0145-8 pmid:30956928 pmcid:PMC6417456 fatcat:psbvulhqzfervggettvlabv2jm

MARVEL - D2.1: Collection and Analysis of Experimental Data

Adrian Muscat
2021 Zenodo  
This knowledge determines how and where the audio-visual data is collected and annotated.  ...  The volume and velocity at which data is collected and moved from one network layer to another are estimated from the technical specifications of the devices as well as from the expected output of the  ...  Matching of the datasets to the AI tasks and AI-based components, assuming the annotations are collected.  ... 
doi:10.5281/zenodo.5052713 fatcat:kyyonzu3ijdjrcrkmyf2y347yy
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