Biblio
Filters: Author is Emilia Gómez [Clear All Filters]
Generating data to train convolutional neural networks for classical music source separation.
Proceedings of the 14th Sound and Music Computing Conference. 227-233.
(2017).
Fundamental frequency alignment vs note-based melodic similarity for singing voice assessment.
8th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).
(2013).
From Heuristics-Based to Data-Driven Audio Melody Extraction.
Department of Information and Communication Technologies. Abstract
(2017).
A Framework for Multi-f0 Modeling in SATB Choir Recordings.
Sound and Music Computing Conference. 447-453. Abstract
(2019).
Forum on transcription.
Twentieth-Century Music. 11(1), 101-161.
(2014).
FlaBase: Towards the Creation of a Flamenco Music Knowledge Base.
16th International Society for Music Information Retrieval Conference. Abstract
(2015).
Evaluation and Combination of Pitch Estimation Methods for Melody Extraction in Symphonic Classical Music.
Journal of New Music Research . 45(2), 101-117.
(2016).
(2006).
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
(2004).
ESSENTIA: an Open-Source Library for Sound and Music Analysis.
ACM International Conference on Multimedia (MM'13). 855-858. Abstract
(2013).
ESSENTIA: an open source library for audio analysis.
ACM SIGMM Records. 6(1), Abstract
(2014).
ESSENTIA: an Audio Analysis Library for Music Information Retrieval.
International Society for Music Information Retrieval Conference (ISMIR'13). 493-498. Abstract
(2013).
End-to-End Sound Source Separation Conditioned On Instrument Labels.
2019 International Conference on Acoustics, Speech, and Signal Processing. Abstract
(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
(2019).
Discovering Expressive Transformation Rules from Saxophone Jazz Performances.
Journal of New Music Research. 34, 319-330. Abstract
(2005).
The Discipline formerly known as MIR.
International Society for Music Information Retrieval (ISMIR) Conference, special session on The Future of MIR (fMIR). Abstract
(2009).
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.
(2018).
Da-TACOS: A dataset for cover song identification and understanding.
International Society for Music Information Retrieval (ISMIR). Abstract
(2019).
A cover song identification system based on sequences of tonal descriptors.
Music Information Retrieval Evaluation eXchange (MIREX) extended abstract. Abstract
(2007).
Correspondence between audio and visual deep models for musical instrument detection in video recordings.
18th International Society for Music Information Retrieval Conference (ISMIR2017, LBD). Abstract
(2017).
Correlations Between Musical Descriptors and Emotions Recognized in Beethoven’s Eroica.
Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music (ESCOM). Abstract
(2015).
Contextual set-class analysis.
( , Ed.).Computational Music Analysis. 81-110. Abstract
(2015).
A Content-based System for Music Recommendation and Visualization of User Preferences Working on Semantic Notions.
9th International Workshop on Content-based Multimedia Indexing. Abstract
(2011).
(2011).
Content-based music recommendation based on user preference examples.
The 4th ACM Conference on Recommender Systems. Workshop on Music Recommendation and Discovery (Womrad 2010). Abstract
(2010).