Visualitza per autoria "Porter, Alastair"

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  • A tool for the analysis and discovery of Ottoman-Turkish Makam music
    Sentürk, Sertan; Ferraro, Andrés; Porter, Alastair; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2016)
    We present a web application for the analysis and discovery of Ottoman-Turkish makam music. The tool uses an audio-score alignment methodology developed for this music culture for the analysis. It stores the data to be ...
  • AcousticBrainz: a community platform for gathering music information obtained from audio
    Porter, Alastair; Bogdanov, Dmitry; Kaye, Robert; Tsukanov, Roman; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2015)
    We introduce the AcousticBrainz project, an open platform for gathering music information. At its core, AcousticBrainz is a database of music descriptors computed from audio recordings using a number of state-of-the-art ...
  • An Analysis and storage system for music research datasets
    Porter, Alastair; Serra, Xavier (ACM Association for Computer Machinery, 2014)
    We present a work ow processing and data storage system that has been developed to store the computational analysis of large databases of music-related documents. Documents can consist of any music-related data, for ...
  • Cross-collection evaluation for music classification tasks
    Bogdanov, Dmitry; Porter, Alastair; Herrera Boyer, Perfecto, 1964-; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2016)
    Many studies in music classification are concerned with obtaining the highest possible cross-validation result. However, some studies have noted that cross-validation may be prone to biases and that additional evaluations ...
  • Dunya: a system for browsing audio music collections exploiting cultural context
    Porter, Alastair; Sordo, Mohamed; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2013)
    Music recommendation and discovery is an important MIR application with a strong impact in the music industry, but most music recommendation systems are still quite generic and without much musical knowledge. In this paper ...
  • Freesound datasets: a platform for the creation of open audio datasets
    Fonseca, Eduardo; Pons Puig, Jordi; Favory, Xavier; Font Corbera, Frederic; Bogdanov, Dmitry; Ferraro, Andrés; Oramas, Sergio; Porter, Alastair; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2017)
    Openly available datasets are a key factor in the advancement of data-driven research approaches, including many of the ones used in sound and music computing. In the last few years, quite a number of new audio datasets ...
  • Interweaving and enriching digital music collections for scholarship, performance, and enjoyment
    Weigl, David M.; Goebl, Werner; Crawford, Tim; Gkiokas, Aggelos; Gutiérrez Páez, Nicolás Felipe; Porter, Alastair; Santos Rodríguez, Patrícia; Karreman, Casper; Vroomen, Ingmar; Liem, Cynthia C. S.; Sarasúa Berodia, Álvaro; van Tilburg, Marcel (ACM Association for Computer Machinery, 2019)
    The turn toward the digital has opened up previously difficult to access musical materials to wider musicological scholarship. Digital repositories provide access to publicly licensed score images, score encodings, textual ...
  • MediaEval 2018 AcousticBrainz genre task: A baseline combining deep feature embeddings across datasets
    Oramas, Sergio; Bogdanov, Dmitry; Porter, Alastair (CEUR Workshop Proceedings, 2018)
    In this paper we present a baseline approach for the MediaEval 2018 AcousticBrainz Genre Task that takes advantage of stacking multiple feature embeddings learned on individual genre datasets by simple deep learning ...
  • MediaEval 2019: emotion and theme recognition in music using Jamendo
    Bogdanov, Dmitry; Porter, Alastair; Tovstogan, Philip; Won, Minz (CEUR Workshop Proceedings, 2019)
    This paper provides an overview of the Emotion and Theme recognition in Music task organized as part of the MediaEval 2019 Benchmarking Initiative for Multimedia Evaluation. The goal of this task is to automatically ...
  • Mining metadata from the web for AcousticBrainz
    Porter, Alastair; Bogdanov, Dmitry; Serra, Xavier (ACM Association for Computer Machinery, 2016)
    Semantic annotations of music collections in digital libraries are important for organization and navigation of the collection. These annotations and their associated metadata are useful in many Music Information Retrieval ...
  • Taming wild horses with Essentia Music Extractor
    Bogdanov, Dmitry; Porter, Alastair; Serra, Xavier (International Society for Music Information Retrieval (ISMIR), 2015)
    We overview the work done on automatic music audio description using the Essentia Music Extractor. We have successfully applied this tool to the analysis on a large scale in the AcousticBrainz project, in which we have ...
  • The AcousticBrainz genre dataset: Multi-source, multi-level, multi-label, and large-scale
    Bogdanov, Dmitry; Porter, Alastair; Schreiber, Hendrik; Urbano, Julián; Oramas, Sergio (International Society for Music Information Retrieval (ISMIR), 2019)
    This paper introduces the AcousticBrainz Genre Dataset, a large-scale collection of hierarchical multi-label genre annotations from different metadata sources. It allows researchers to explore how the same music pieces ...
  • The MediaEval 2017 AcousticBrainz genre task: content-based music genre recognition from multiple sources
    Bogdanov, Dmitry; Porter, Alastair; Urbano, Julián; Schreiber, Hendrik (CEUR Workshop Proceedings, 2017)
    This paper provides an overview of the AcousticBrainz Genre Task organized as part of the MediaEval 2017 Benchmarking Initiative for Multimedia Evaluation. The task is focused on content-based music genre recognition ...
  • The MediaEval 2018 AcousticBrainz genre task: content-based music genre recognition from multiple sources
    Bogdanov, Dmitry; Porter, Alastair; Urbano, Julián; Schreiber, Hendrik (CEUR Workshop Proceedings, 2018)
    This paper provides an overview of the AcousticBrainz Genre Task organized as part of the MediaEval 2018 Benchmarking Initiative for Multimedia Evaluation. The task is focused on content-based music genre recognition ...
  • The MTG-Jamendo dataset for automatic music tagging
    Bogdanov, Dmitry; Won, Minz; Tovstogan, Philip; Porter, Alastair; Serra, Xavier (ICML, 2019)
    We present the MTG-Jamendo Dataset, a new open dataset for music auto-tagging. It is built using music available at Jamendo under Creative Commons licenses and tags provided by content uploaders. The dataset contains ...
  • TROMPA-MER: an open dataset for personalized music emotion recognition
    Gómez Cañón, Juan Sebastián; Gutiérrez Páez, Nicolás Felipe; Porcaro, Lorenzo; Porter, Alastair; Cano, Estefanía; Herrera Boyer, Perfecto, 1964-; Gkiokas, Aggelos; Santos Rodríguez, Patrícia; Hernández Leo, Davinia; Karreman, Casper; Gómez Gutiérrez, Emilia, 1975- (Springer, 2023)
    We present a platform and a dataset to help research on Music Emotion Recognition (MER). We developed the Music Enthusiasts platform aiming to improve the gathering and analysis of the so-called “ground truth” needed as ...

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