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A Closer Look On Artist Filters For Musical Genre Classification

Arthur Flexer
2007 Zenodo  
The second shows the effect of artist filters on the choice of features used for genre classification. 3.1 Experiment 1: one model per song versus one model per genre The following approach based on spectral  ...  It can be argued that in such a scenario one is doing artist classification rather than genre classification. Specific mastering and production effects could also play a role in such a scenario.  ... 
doi:10.5281/zenodo.1415668 fatcat:dffdwaxvc5buznxr37ubiey2me

Making Large Music Collections Accessible using Enhanced Metadata and Lightweight Visualizations

Florian Kleedorfer, Ulf Harr, Brigitte Krenn
2007 Third International Conference on Automated Production of Cross Media Content for Multi-Channel Distribution (AXMEDIS'07)  
We present stategies for improving the accessibility of large music archives intended for use in commercial environments like music download platforms.  ...  Our approach is based on metadata enhancement and on the augmentation of traditional browsing interfaces with concise data visualizations.  ...  We would like to thank David Mann for proficiently programming much of the application and Mandakini Pachauri for keeping us up to date with the latest developments in commercial music download platforms  ... 
doi:10.1109/axmedis.2007.28 fatcat:kgq6pmuurvd6xjn4k7xod7zn44

Investigating Web-Based Approaches to Revealing Prototypical Music Artists in Genre Taxonomies

Markus Schedl, Peter Knees, Gerhard Widmer
2007 2006 1st International Conference on Digital Information Management  
More precisely, we try to find prototypical music artists for each genre in a given real-world taxonomy.  ...  First, we model and evaluate a classification task to determine accuracies.  ...  FOR THE GENRES HEAVY METAL AND FOLK FOR EACH OF THE THREE APPROACHES.and Filter.  ... 
doi:10.1109/icdim.2007.369245 dblp:conf/icdim/SchedlKW06 fatcat:biivm234wbhbrakhzidygffdqm

Evaluation Of Mfcc Estimation Techniques For Music Similarity

Mads Christensen, Jesper Jensen, Søren Holdt Jensen, Manohar Murthi
2006 Zenodo  
For instance, in speech there is only one excitation signal, while in music there may be an excitation signal and a filter for each instrument.  ...  [16] , genre classification is an easy, meaningful method for evaluating music similarity [7, 17] . The underlying assumption is that songs from the same genre are musically similar.  ... 
doi:10.5281/zenodo.52739 fatcat:hwqcetbcqvf4dllficbt6y3oke

Social Tagging and Music Information Retrieval

Paul Lamere
2008 Journal of New Music Research  
Captured in these tags is a great deal of information that is highly relevant to Music Information Retrieval (MIR) researchers including information about genre, mood, instrumentation, and quality.  ...  In this article, we describe the state of the art in commercial and research social tagging systems for music. We describe how tags are collected and used in current systems.  ...  A closer look shows that Last.fm taggers will often apply the "Classical" tag to artists that employ a backing orchestra.  ... 
doi:10.1080/09298210802479284 fatcat:ztwamgwh2ngd7mmntzlp6pl5u4

Artist Classification With Web-Based Data

Peter Knees, Elias Pampalk, Gerhard Widmer
2004 Zenodo  
The Austrian Research Institute for Artificial Intelligence is supported by the Austrian Federal Ministry for Education, Science, and Culture and by the Austrian Federal Ministry for Transport, Innovation  ...  First, a very small one with 25 artists for which genre classification results have been published by Whitman and Smaragdis [29] .  ...  For example, genres can help located an album in a record store or discover similar artists. One of the main drawbacks of genres is the time-consuming necessity to classify music manually.  ... 
doi:10.5281/zenodo.1417189 fatcat:7n65s4rc4fec3afhdx3cnjj3ym

Additional Evidence That Common Low-Level Features Of Individual Audio Frames Are Not Representative Of Music Genre

Gonçalo Marques, Miguel Lopes, Mohamed Sordo, Thibault Langlois, Fabien Gouyon
2010 Proceedings of the SMC Conferences  
We used an artist filter [9, 10] to ensure that the music pieces from a specific artist are present in one and only one of the three folds.  ...  As in the original ISMIR 2004 contest, the dataset does not account for artist filtering between both sets.  ... 
doi:10.5281/zenodo.849711 fatcat:ufkqr3wbsrf27hpyirz3aypyyq

Improving The Reliability Of Music Genre Classification Using Rejection And Verification

Alessandro L. Koerich
2013 Zenodo  
The splitting is done using an artist filter, which places the music pieces of an specific artist exclusively in one, and only one, fold of the dataset.  ...  and the types of classifiers used for different classification tasks such as music genre classification, mood classification, artist identification, instrument recognition and music annotation.  ... 
doi:10.5281/zenodo.1416569 fatcat:aeqew5mwzfcqpiu3hs3fcmu2ai

Audio Cover Song Identification: Mirex 2006-2007 Results And Analyses

J. Stephen Downie, Mert Bay, Andreas F. Ehmann, M. Cameron Jones
2008 Zenodo  
Additionally, we would like to thank Professor David Dubin for his statistical advice.  ...  [9] addressed similar effects, where they evaluated genre classification systems on artist-filtered datasets and noted a marked reduction in performance.  ...  In the 2007 Audio Genre Classification task, the data was filtered such that no track from the same artist could simultaneously exist in both the test and train sets in any cross-validation fold.  ... 
doi:10.5281/zenodo.1417133 fatcat:6scfommxuvf7zoo26xepcmo3fm

Inferring similarity between music objects with application to playlist generation

R. Ragno, C. J. C. Burges, C. Herley
2005 Proceedings of the 7th ACM SIGMM international workshop on Multimedia information retrieval - MIR '05  
In this paper we describe a simple way to automatically infer similarities between objects based on their occurrences in an authored stream. The method works both for audio and video.  ...  entities, such as artists.  ...  Note that artists of similar genres and styles are closer together.  ... 
doi:10.1145/1101826.1101840 dblp:conf/mir/RagnoBH05 fatcat:mqdvzy4fxzc4zgqyikxcjkpcke

Knowledge Extraction And Representation Learning For Music Recommendation And Classification

Sergio Oramas, Xavier Serra
2017 Zenodo  
Next, we focus on learning new data representations from multimodal content using deep learning architectures, addressing the problems of cold-start music recommendation and multi-label music genre classification  ...  We focus on the semantic enrichment of descriptions associated to musical items (e.g., artists biographies, album reviews, metadata), and the exploitation of multimodal data (e.g., text, audio, images)  ...  Then, we focus on three specific MIR tasks: music genre classification, artist similarity, and music recommendation.  ... 
doi:10.5281/zenodo.1100973 fatcat:yfpmc6qxbbakjp6qzvywyoaoci

Knowledge Extraction And Representation Learning For Music Recommendation And Classification

Sergio Oramas, Xavier Serra
2017 Zenodo  
Next, we focus on learning new data representations from multimodal content using deep learning architectures, addressing the problems of cold-start music recommendation and multi-label music genre classification  ...  We focus on the semantic enrichment of descriptions associated to musical items (e.g., artists biographies, album reviews, metadata), and the exploitation of multimodal data (e.g., text, audio, images)  ...  Then, we focus on three specific MIR tasks: music genre classification, artist similarity, and music recommendation.  ... 
doi:10.5281/zenodo.1048497 fatcat:kdh5jhvocbh3riwln6n2f756su

Automatic Generation of Social Tags for Music Recommendation

Douglas Eck, Paul Lamere, Thierry Bertin-Mahieux, Stephen Green
2007 Neural Information Processing Systems  
The resulting automatic tags (or autotags) furnish information about music that is otherwise untagged or poorly tagged, allowing for insertion of previously unheard music into a social recommender.  ...  In this paper, we propose a method for predicting these social tags directly from MP3 files. Using a set of boosted classifiers, we map audio features onto social tags collected from the Web.  ...  The dataset used for these experiments is already larger than those used for published results for genre and artist classification.  ... 
dblp:conf/nips/EckLBG07 fatcat:sghfw3lcbnhwjdsprnichbskim

Classification accuracy is not enough

Bob L. Sturm
2013 Journal of Intelligent Information Systems  
A recent review of works in MGR since 1995 shows that most (82 %) measure the capacity of a system to recognize genre by its classification accuracy.  ...  After reviewing evaluation in MGR, we show that neither classification accuracy, nor recall and precision, nor confusion tables, necessarily reflect the capacity of a system to recognize genre in musical  ...  Sturm for her bibliographic prowess; and Geraint Wiggins, Nick Collins, Matthew Davies, Fabien Gouyon, Arthur Flexer, and Mark Plumbley for numerous and insightful conversations.  ... 
doi:10.1007/s10844-013-0250-y fatcat:kwoquuwuajhrnp7btbth2ke264

Contextual music information retrieval and recommendation: State of the art and challenges

Marius Kaminskas, Francesco Ricci
2012 Computer Science Review  
This survey covers a broad range of topics, starting from classical music information retrieval (MIR) and recommender system (RS) techniques, and then focusing on context-aware music applications as well  ...  The basic idea is to retrieve and suggest music depending on the user's actual situation, for instance emotional state, or any other contextual conditions that might influence the user's perception of  ...  For instance: searching for rock songs is a task at a genre level; looking for artists similar to Björk is clearly a task at an artist level; finding cover versions of the song "Let it Be" by The Beatles  ... 
doi:10.1016/j.cosrev.2012.04.002 fatcat:eheqwtlpufftni2k4sgolnskli
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