Add to ORKGInternational audienceThis paper presents the participation to the MusiClef 2012 Multimodal Music Tagging task. It expounds the approach that consists of an aggregation of estimators as a procedure to combine different sources of information
Comunicació presentada a: ML4MD Machine Learning for Music Discovery Workshop del congrés ICML2019 c...
Music auto-tagging refers to automatically assigning seman-tic labels (tags) such as genre, mood and...
Bagging is one the most classic ensemble learning techniques in the machine learning literature. The...
International audienceThis paper presents the participation to the MusiClef 2012 Multimodal Music Ta...
10.1145/1835449.1835555SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Re...
MusiClef is a multimodal music benchmarking initiative that will be running a MediaEval 2012 Brave ...
This paper presents the MusiClef data set, a multimodal data set of professionally annotated music. ...
Tags constitute a very useful tool for multimedia document indexing. This PhD thesis deals with auto...
to describe different aspects of a music clip. With the explosive growth of digital music available ...
Les tags constituent un outil très utile pour indexer des documents multimédias. Cette thèse de doct...
In this work we propose a set of new automatic text augmentations that leverage Large Language Model...
Audio tags correspond to keywords that people use to de-scribe different aspects of a music clip, su...
As music distribution has evolved form physical media to digital content, tens of millions of songs ...
cote interne IRCAM: Orio12bNone / NoneNational audienceMusiclef : Multimodal music tagging tas
One of the many challenges of machine learning are systems for automatic tagging of music, the compl...
Comunicació presentada a: ML4MD Machine Learning for Music Discovery Workshop del congrés ICML2019 c...
Music auto-tagging refers to automatically assigning seman-tic labels (tags) such as genre, mood and...
Bagging is one the most classic ensemble learning techniques in the machine learning literature. The...
International audienceThis paper presents the participation to the MusiClef 2012 Multimodal Music Ta...
10.1145/1835449.1835555SIGIR 2010 Proceedings - 33rd Annual International ACM SIGIR Conference on Re...
MusiClef is a multimodal music benchmarking initiative that will be running a MediaEval 2012 Brave ...
This paper presents the MusiClef data set, a multimodal data set of professionally annotated music. ...
Tags constitute a very useful tool for multimedia document indexing. This PhD thesis deals with auto...
to describe different aspects of a music clip. With the explosive growth of digital music available ...
Les tags constituent un outil très utile pour indexer des documents multimédias. Cette thèse de doct...
In this work we propose a set of new automatic text augmentations that leverage Large Language Model...
Audio tags correspond to keywords that people use to de-scribe different aspects of a music clip, su...
As music distribution has evolved form physical media to digital content, tens of millions of songs ...
cote interne IRCAM: Orio12bNone / NoneNational audienceMusiclef : Multimodal music tagging tas
One of the many challenges of machine learning are systems for automatic tagging of music, the compl...
Comunicació presentada a: ML4MD Machine Learning for Music Discovery Workshop del congrés ICML2019 c...
Music auto-tagging refers to automatically assigning seman-tic labels (tags) such as genre, mood and...
Bagging is one the most classic ensemble learning techniques in the machine learning literature. The...