Music Information Retrieval CISUC

 
MOODetector

 
Books

     

 
Theses

  • PDFRicardo Malheiro (2017). “Emotion-based Analysis and Classification of Music Lyrics“. Doctoral Program in Information Science and Technology. University of Coimbra. Supervisor (with the co-supervision of Prof. Dr. Paulo Gomes).
  • PDFPanda R. (2010). “Automatic Mood Tracking in Audio Music”. MSc Thesis, Department of Informatics Engineering, University of Coimbra, Portugal, July 2010.

  • PDFFernandes J. (2010). “Automatic Playlist Generation via Music Mood Analysis”. MSc Thesis, Department of Informatics Engineering, University of Coimbra, Portugal, September 2010.

 
Journal Papers

  • PDF Malheiro R., Panda P., Gomes P. & Paiva R. P. (2016). “Emotionally-Relevant Features for Classification and Regression of Music Lyrics”. IEEE Transactions on Affective Computing (accepted for publication).

  • PDFPanda R., Rocha B., Paiva R. P. (2015). “Music Emotion Recognition with Standard and Melodic Audio Features”. Applied Artificial Intelligence, Vol. 29:4, pp. 313-334, Taylor & Francis.

 
Conference Papers

  • PDFMalheiro R., Panda R., Gomes P. & Paiva R. P. (2016). “Classification and Regression of Music Lyrics: Emotionally-Significant Features”. 8th International Conference on Knowledge Discovery and Information Retrieval – KDIR'2016, Porto, Portugal.

  • PDFMalheiro R., Oliveira H. G., Gomes P. & Paiva R. P. (2016). “Keyword-Based Approach for Lyrics Emotion Variation Detection”. 8th International Conference on Knowledge Discovery and Information Retrieval – KDIR'2016, Porto, Portugal.

  • PDFMalheiro R., Panda R., Gomes P. & Paiva R. P. (2016). “Bi-Modal Music Emotion Recognition: Novel Lyrical Features and Dataset”. 9th International Workshop on Music and Machine Learning – MML'2016 – in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases – ECML/PKDD 2016, Riva del Garda, Italy.

  • PDF Panda R., Malheiro R., Rocha B., Oliveira A. & Paiva R. P. (2013). “Multi-Modal Music Emotion Recognition: A New Dataset, Methodology and Comparative Analysis”. 10th International Symposium on Computer Music Multidisciplinary Research – CMMR’2013, Marseille, France.

  • PDF Panda R., Rocha B., & Paiva R. P. (2013). “Dimensional Music Emotion Recognition: Combining Standard and Melodic Audio Features”. 10th International Symposium on Computer Music Multidisciplinary Research – CMMR’2013, Marseille, France.

  • PDF Rocha B., Panda R. & Paiva R. P. (2013). “Music Emotion Recognition: The Importance of Melodic Features”. 6th International Workshop on Music and Machine Learning – MML’2013 – in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases – ECML/PKDD 2013, Prague, Czech Republic.

  • PDF Malheiro R., Panda R., Gomes P. & Paiva R. P. (2013). “Music Emotion Recognition from Lyrics: A Comparative Study”. 6th International Workshop on Music and Machine Learning – MML’2013 – in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases – ECML/PKDD 2013, Prague, Czech Republic.

  • PDFPanda R and Paiva R. P. (2012). “MIREX 2012: Mood Classifcation Task Submission”. Proceedings of the Music Information Retrieval Exchange – MIREX'2012.

  • PDFPanda R. and Paiva R. P. (2012). “Music Emotion Classification: Dataset Acquisition and Comparative Analysis”. 15th International Conference on Digital Audio Effects – DAFx ’12, York, UK.

  • PDFPanda R. and Paiva R. P. (2012). “Music Emotion Classification: Analysis of a Classifier Ensemble Approach”. 5th International Workshop on Machine Learning and Music – MML ’2012 (at the 29th International Conference on Machine Learning – ICML’2012), Edinburgh, Scotland, UK.

  • PDFCardoso L., Panda R and Paiva R. P. (2011). “MOODetector: A Prototype Software Tool for  Mood-based Playlist Generation”. Simpósio de Informática – INForum 2011, Coimbra, Portugal.

  • PDFPanda R. and Paiva R. P. (2011). “Automatic Creation of Mood Playlists in the Thayer Plane: a Methodology and a Comparative Study”. 8th Sound and Music Computing Conference – SMC’2011, Padova, Italy.

  • PDFPanda R. and Paiva R. P. (2011). “Using Support Vector Machines for Automatic Mood Tracking in Audio Music”. Proceedings of the 130th Audio Engineering Society Convention – AES 130, London, UK.

 
Technical Reports

 

 
Invited Presentations

  • Paiva R. P. (2013). “Music Data Mining: Automatic Emotion Recognition”. Invited Presentation. Ciclo de Conferencias en Ingeniería Informática, Universidad Central del Ecuador, Quito, Ecuador. October 25, 2013.

  • PDF Paiva R. P. (2013). “MOODetector: Automatic Music Emotion Recognition”. Invited Presentation. Campus Party Quito 3, Quito, Equador. September 20, 2013.

  • PDFPaiva R. P. (2012). “From Music Information Retrieval to Music Emotion Recognition”. Internal Presentation. Center for Informatics and Systems of the University of Coimbra, Portugal.

  • PDF Paiva R. P. (2010). “MOODetector: A System for Mood-based Classification and Retrieval of Audio Music”. Invited Presentation. 1as. Jornadas de la Sociedad Ibérica de Tecnología Musical, Madrid, Spain. December 2010.

 

 
Mellodee

 
Books

  • amazon PDFPaiva R. P. (2009). Melody Detection in Polyphonic Audio: From Pitch Extraction to Note Identification”. Lambert Academic Publishing. ISBN 978-3838319704.

 
Theses

  • PDFPaiva R. P. (2007). “Melody Detection in Polyphonic Audio”. PhD Thesis, Department of Informatics Engineering, University of Coimbra, Portugal, February 2007.

 
Journal Papers

  • PDFPaiva R. P., Mendes T. and Cardoso A. (2008). “From Pitches to Notes: Creation and Segmentation of Pitch Tracks for Melody Detection in Polyphonic Audio”. Journal of New Music Research, Vol. 37, No. 3, pp 185-205, Taylor and Francis.

  • PDFPaiva R. P., Mendes T. and Cardoso A. (2006). “Melody Detection in Polyphonic Musical Signals: Exploiting Perceptual Rules, Note Salience and Melodic Smoothness”. Computer Music Journal, Vol. 30, No. 4, pp. 80-98, MIT Press.

 
Conference Papers

  • PDFPaiva R. P. (2007). “An Approach for Melody Extraction from Polyphonic Audio: Using Perceptual Principles and Melodic Smoothness”. Proceedings of the 154th Meeting of the Acoustical Society of America, New Orleans, USA, November 2007.

  • PDF Paiva R. P. (2005). “An Algorithm for Melody Detection in Polyphonic Recordings”. Proceedings of the Music Information Retrieval Exchange – MIREX’2005.

  • PDF Paiva R. P., Mendes T. and Cardoso A. (2005). “On the Detection of Melody Notes in Polyphonic Audio”. Proceedings of the International Conference on Music Information Retrieval – ISMIR’2005, London, UK.

  • PDF Paiva R. P., Mendes T. and Cardoso A. (2005). “Exploiting Melodic Smoothness for Melody Detection in Polyphonic Audio”. Proceedings of the International Computer Music Conference – ICMC’2005, Barcelona, Spain.

  • PDF Paiva R. P., Mendes T. and Cardoso A. (2005). “On the Definition of Musical Notes from Pitch Tracks for Melody Detection in Polyphonic Recordings”. Proceedings of the International Conference on Digital Audio Effects – DAFx’05, Madrid, Spain.

  • PDF Paiva R. P., Mendes T. and Cardoso A. (2005). “Segmentation of Pitch Tracks for Melody Detection in Polyphonic Audio”. Proceedings of the European Signal Processing Conference – EUSIPCO’2005, Antalya, Turkey.

  • PDF Paiva R. P., Mendes T. and Cardoso A. (2005). “An Auditory Model Based Approach for Melody Detection in Polyphonic Musical Recordings”. U. K. Wiil (ed.) Computer Music Modeling and Retrieval – CMMR 2004, Esbjerg, Denmark, Lecture Notes in Computer Science, Vol. 3310, pp. 21-40.

  • PDF Paiva R. P., Mendes T. and Cardoso A. (2004). A Methodology for Detection of Melody in Polyphonic Musical Signals. Proceedings of the 116th Audio Engineering Society Convention – AES 116, Berlim, Germany.

 
Technical Reports

  • PDF Gómez E., Streich S., Ong B., Paiva R. P., Tappert S., Batke J.-M., Poliner G., Ellis D. and Bello J. P. (2006). A Quantitative Comparison of Different Approaches for Melody Extraction from Polyphonic Audio Recordings. Technical Report, Music Technology Group, Pompeu Fabra University, Spain.

 
Invited Presentations

  • PDF Paiva R. P. (2007). “Melody Detection in Polyphonic Audio”. Invited Presentation. 9th Meeting of APEA - Associação Portuguesa de Engenharia Áudio (national branch of the Audio Engineering Society), Leiria, Portugal. October 20, 2007.