This paper presents the MusiClef data set, a multimodal data set of professionally annotated music. It includes editorial meta-data about songs, albums, and artists, as well as MusicBrainz identifiers to facilitate linking to other data sets. In addition, several audio features (generic low-level descriptors and state-of-the-art music features) are provided. 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. Versions of this data set were used in the MusiCLEF 2011 and in the MusiClef 2012 evaluation campaigns for auto-tagging tasks
Comunicació presentada al 2nd CompMusic Workshop, celebrat els dies 12 i 13 de juliol de 2012 a Ista...
In this paper, we describe the LFM-1b User Genre Profile dataset. It provides detailed information o...
The main objective of the “Metadata Used in Semantic Indexes and Charts” (MUSIC) project is to facil...
This paper presents the MusiClef data set, a multimodal data set of professionally annotated music. ...
This paper introduces the AcousticBrainz Genre Dataset, a large-scale collection of hierarchical mul...
MusiCLEF is a novel benchmarking activity that aims at promoting the development of new methodologie...
This paper introduces the AcousticBrainz Genre Dataset, a large-scale collection of hierarchical mul...
This paper introduces the AcousticBrainz Genre Dataset, a large-scale collection of hierarchical mul...
Comunicació presentada a: 20th International Society for Music Information Retrieval Conference cele...
MusiClef is a multimodal music benchmarking initiative that will be running a MediaEval 2012 Brave ...
Comunicació presentada al 3rd International Workshop on Digital Libraries for Musicology, celebrat e...
This work presents the rationale, tasks and procedures of MusiCLEF, a novel benchmarking activity th...
The AcousticBrainz Genre Dataset consists of four datasets of genre annotations and music features e...
In the MuziK project we try to automate the typically hard task of annotating music files manually. ...
This dataset contains AllMusic ground-truth genre annotations and is complementary to the rest of th...
Comunicació presentada al 2nd CompMusic Workshop, celebrat els dies 12 i 13 de juliol de 2012 a Ista...
In this paper, we describe the LFM-1b User Genre Profile dataset. It provides detailed information o...
The main objective of the “Metadata Used in Semantic Indexes and Charts” (MUSIC) project is to facil...
This paper presents the MusiClef data set, a multimodal data set of professionally annotated music. ...
This paper introduces the AcousticBrainz Genre Dataset, a large-scale collection of hierarchical mul...
MusiCLEF is a novel benchmarking activity that aims at promoting the development of new methodologie...
This paper introduces the AcousticBrainz Genre Dataset, a large-scale collection of hierarchical mul...
This paper introduces the AcousticBrainz Genre Dataset, a large-scale collection of hierarchical mul...
Comunicació presentada a: 20th International Society for Music Information Retrieval Conference cele...
MusiClef is a multimodal music benchmarking initiative that will be running a MediaEval 2012 Brave ...
Comunicació presentada al 3rd International Workshop on Digital Libraries for Musicology, celebrat e...
This work presents the rationale, tasks and procedures of MusiCLEF, a novel benchmarking activity th...
The AcousticBrainz Genre Dataset consists of four datasets of genre annotations and music features e...
In the MuziK project we try to automate the typically hard task of annotating music files manually. ...
This dataset contains AllMusic ground-truth genre annotations and is complementary to the rest of th...
Comunicació presentada al 2nd CompMusic Workshop, celebrat els dies 12 i 13 de juliol de 2012 a Ista...
In this paper, we describe the LFM-1b User Genre Profile dataset. It provides detailed information o...
The main objective of the “Metadata Used in Semantic Indexes and Charts” (MUSIC) project is to facil...