In this paper, an approach for music genre classification based on sparse representation using MARSYAS features is proposed. The MARSYAS feature descriptor consisting of timbral texture, pitch and beat related features is used for the classification of music genre. On-line Dictionary Learning (ODL) is used to achieve sparse representation of the features for developing dictionaries for each musical genre. We demonstrate the efficacy of the proposed framework on the Latin Music Database (LMD) consisting of over 3000 tracks spanning 10 genres namely Axé, Bachata, Bolero, Forró, Gaúcha, Merengue, Pagode, Salsa, Sertaneja and Tango
Modern digital music libraries are huge. Searching and retrieving requested piece of music is challe...
Abstract — this paper presents a dynamic ensemble selection method for music genre classification wh...
This thesis explores the ideas of feature learning and sparse coding for Music Information Retrieval...
This paper presents a simple, but efficient and robust, method for music genre classification that u...
This paper presents a novel approach to the task of automatic music genre classification which is ba...
Presented at the Drexel IEEE Graduate Forum’s Fifth Annual Research SymposiumIn this study we evalua...
Music genres can be seen as categorical descriptions used to classify music basing on various charac...
This paper presents a novel approach to the task of automatic music genre classification which is ba...
A novel framework for music genre classification, namely the joint sparse low-rank representation (J...
This paper presents a non-conventional approach for the automatic music genre classification problem...
This paper presents a non-conventional approach for the automatic music genre classification problem...
Presented at the ACM Multimedia 2011 Doctoral Symposium Poster, Scottsdale, Arizona, USA.Music genre...
Musical genre classification is put into context byexplaining about the structures in music and how ...
The field of music and speech classification is quite\ud mature with researchers having settled on t...
This paper presents the results of the application of a feature selection procedure to an automatic ...
Modern digital music libraries are huge. Searching and retrieving requested piece of music is challe...
Abstract — this paper presents a dynamic ensemble selection method for music genre classification wh...
This thesis explores the ideas of feature learning and sparse coding for Music Information Retrieval...
This paper presents a simple, but efficient and robust, method for music genre classification that u...
This paper presents a novel approach to the task of automatic music genre classification which is ba...
Presented at the Drexel IEEE Graduate Forum’s Fifth Annual Research SymposiumIn this study we evalua...
Music genres can be seen as categorical descriptions used to classify music basing on various charac...
This paper presents a novel approach to the task of automatic music genre classification which is ba...
A novel framework for music genre classification, namely the joint sparse low-rank representation (J...
This paper presents a non-conventional approach for the automatic music genre classification problem...
This paper presents a non-conventional approach for the automatic music genre classification problem...
Presented at the ACM Multimedia 2011 Doctoral Symposium Poster, Scottsdale, Arizona, USA.Music genre...
Musical genre classification is put into context byexplaining about the structures in music and how ...
The field of music and speech classification is quite\ud mature with researchers having settled on t...
This paper presents the results of the application of a feature selection procedure to an automatic ...
Modern digital music libraries are huge. Searching and retrieving requested piece of music is challe...
Abstract — this paper presents a dynamic ensemble selection method for music genre classification wh...
This thesis explores the ideas of feature learning and sparse coding for Music Information Retrieval...