Biblio

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Gómez Cañón, J. S., Herrera P., Gómez E., & Cano E. (2019).  The emotions that we perceive in music: the influence of language and lyrics comprehension on agreement. Workshop-Symposium on Research Methods in Music and Emotion. Abstract
Gómez, E., Guastavino C., Gómez F., & Bonada J. (2012).  Analyzing Melodic Similarity Judgements in Flamenco a Cappella Singing. International Conference on Music Perception and Cognition.
application/pdf iconICMPC-2012-flamenco.pdf
Gómez, E., Cano P., Gomes L., Batlle E., & Bonnet M. (2002).  Mixed Watermarking-Fingerprinting Approach for Integrity Verification of Audio Recordings. Abstract
Gómez, E., & Herrera P. (2004).  Automatic Extraction of Tonal Metadata from Polyphonic Audio Recordings. AES. Abstract
Gómez, V. (2002).  Estudi de diferents algorismes d'entrenament de xarxes neuronals de funció de base radial.
Gómez, F., Pikrakis A., Mora J., Díaz-Báñez J. M., & Gómez E. (2011).  Automatic Detection of Ornamentation in Flamenco Music. 4th International Workshop on Machine Learning and Music, Held in Conjunction with the 25th Annual Conference on Neural Information Processing Systems (NIPS 2011).
application/pdf iconMML-paper-2011.pdf
Gómez, E., Grachten M., Hanjalic A., Janer J., Jordà S., Julià C. F., et al. (2013).  PHENICX: Performances as Highly Enriched aNd Interactive Concert Experiences. SMAC Stockholm Music Acoustics Conference 2013, SMC Sound and Music Computing Conference 2013.
application/pdf iconPHENICX-smac2013-6.0.pdf
Gómez, E., & Bonada J. (2005).  Tonality visualization of polyphonic audio. Abstract
Gómez, E., & Herrera P. (2008).  Comparative Analysis of Music Recordings from Western and Non-Western traditions by Automatic Tonal Feature Extraction. Empirical Musicology Review. 3(3), 140-156. Abstract
Gomez, E., Blaauw M., Bonada J., Chandna P., & Cuesta H. (2018).  Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners. Keynote speech, 2018 Joint Workshop on Machine Learning for Music. The Federated Artificial Intelligence Meeting (FAIM), a joint workshop program of ICML, IJCAI/ECAI, and AAMAS.
Gómez, E., & Herrera P. (2006).  The song remains the same identifying versions of the same piece using tonal descriptors. Abstract
Gómez, E., & Herrera P. (2008).  Comparative analysis of music recordings from western and non-western traditions by automatic tonal feature extraction and data mining. 4th Conference on Interdisciplinary Musicology (CIM08).
Gómez, E. (2011).  Integrating Different Knowledge Sources for the Computational Modeling of Flamenco Music. (Müller, M., Goto, M., Dixon, S., Ed.).Multimodal Music Processing (Dagstuhl Seminar 11041) - Dagstuhl Reports. 1(1), 82-83. Abstract
Gómez, E., & Herrera P. (2006).  Evaluation and applications of tonal profiles for automatic music tonality description. Abstract
Gómez, E., Cañadas F., Salamon J., Bonada J., Vera P., & Cabañas P. (2012).  Predominant Fundamental Frequency Estimation vs Singing Voice Separation for the Automatic Transcription of Accompanied Flamenco Singing. 13th International Society for Music Information Retrieval Conference (ISMIR 2012). Abstract
application/pdf iconMTGUJA-ISMIR2012-FINAL.pdf
Gómez, E. (2006).  Tonal description of polyphonic audio for music content processing. INFORMS Journal on Computing, Special Cluster on Computation in Music. 18, Abstract
Gómez, E., Bonada J., & Salamon J. (2012).  Automatic Transcription of Flamenco Singing from Monophonic and Polyphonic Music Recordings. III Interdisciplinary Conference on Flamenco Research (INFLA) and II International Workshop of Folk Music Analysis (FMA). Abstract
application/pdf iconINFLA-FMA-Transcription_web.pdf
Gómez, E. (2005).  Key estimation from polyphonic audio. Abstract
Gómez, E., Haro M., & Herrera P. (2009).  Music and geography: content description of musical audio from different parts of the world. 10th International Society for Music Information Retrieval Conference. Abstract
Gómez, E., Grachten M., Amatriain X., & Arcos J. L. (2003).  Melodic characterization of monophonic recordings for expressive tempo transformations. Abstract
Gómez, E., Schedl M., Serra X., & Hu X. (2016).  Music Information Retrieval:
 Overview, Recent Developments and Future Challenges. 17th International Society for Music Information Retrieval (ISMIR) Conference. 11-12. Abstract
Gómez, E., Gouyon F., Herrera P., & Amatriain X. (2003).  Using and enhancing the current MPEG-7 standard for a music content processing tool. Abstract
Gómez, E., & Bonada J. (2013).  Towards Computer-Assisted Flamenco Transcription: An Experimental Comparison of Automatic Transcription Algorithms As Applied to A Cappella Singing. Computer Music Journal. 37(2), 73-90.
Gómez, E., & Herrera P. (2004).  Estimating The Tonality Of Polyphonic Audio Files Cognitive Versus Machine Learning Modelling Strategies. 5th International Society for Music Information Retrieval (ISMIR) Conference. 92-95. Abstract
application/pdf iconGómezHerrera-ISMIR-2004-page-92.pdf
Gómez, E., Guerrero A., & Rodríguez S. (2018).  CANTE FLAMENCO TECH: Aprendizaje del cante con la ayuda de la tecnología. V Congreso Interdisciplinar INVESTIGACIÓN Y FLAMENCO (INFLA). Abstract
application/pdf iconcante-flamenco-tech.pdf
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