Visualitza per autoria "Cuesta, Helena"

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  • A deep-learning based framework for source separation, analysis, and synthesis of choral ensembles
    Chandna, Pritish; Cuesta, Helena; Petermann, Darius; Gómez Gutiérrez, Emilia, 1975- (Frontiers, 2022)
    Choral singing in the soprano, alto, tenor and bass (SATB) format is a widely practiced and studied art form with significant cultural importance. Despite the popularity of the choral setting, it has received little attention ...
  • A Framework for multi-f0 modeling in SATB choir recordings
    Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975-; Chandna, Pritish (Sound and Music Computing, 2019)
    Fundamental frequency (f0) modeling is an important but relatively unexplored aspect of choir singing. Performance evaluation as well as auditory analysis of singing, whether individually or in a choir, often depend on ...
  • Analysis of intonation in unison choir singing
    Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975-; Martorell Domínguez, Agustín; Loáiciga, Felipe (2018)
    Choir singers synchronize their fundamental frequency (f0) and timing when they perform together. In this work, we investigate several expressive characteristics of choir singing, with special emphasis on unison ...
  • Automatic structure detection and visualization in symphonic music
    Cuesta, Helena (2015-12-11)
    Music is perceived as an organized entity where the information is divided in different parts or segments. People with musical training are able to classify these segments according to their musical content or their ...
  • Automatic transcription of flamenco guitar falsetas
    Rodríguez, Sonia; Gómez Gutiérrez, Emilia, 1975-; Cuesta, Helena (Folk Music Analysis, 2018)
    This work deals with the automatic transcription and characterization of flamenco guitar, with a focus on short melodic interludes improvised between sung verses. These are called falsetas in the flamenco argot and are ...
  • Cough-based COVID-19 detection with contextual attention convolutional neural networks and gender information
    Mallol Ragolta, Adrià; Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975-; Schuller, Björn (International Speech Communication Association (ISCA), 2021)
    The aim of this contribution is to automatically detect COVID19 patients by analysing the acoustic information embedded in coughs. COVID-19 affects the respiratory system, and, consequently, respiratory-related signals ...
  • Data-driven pitch content description of choral singing recordings
    Cuesta, Helena (Universitat Pompeu Fabra, 2022-03-28)
    Ensemble singing is a well-established practice across cultures, found in a great diversity of forms, languages, and levels. However, it has not been widely studied in the field of Music Information Retrieval (MIR), likely ...
  • A deep learning based analysis-synthesis framework for unison singing
    Chandna, Pritish; Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975- (International Society for Music Information Retrieval (ISMIR), 2020)
    Unison singing is the name given to an ensemble of singers simultaneously singing the same melody and lyrics. While each individual singer in a unison sings the same principle melody, there are slight timing and pitch ...
  • Deep learning based source separation applied to choir ensembles
    Petermann, Darius; Chandna, Pritish; Cuesta, Helena; Bonada, Jordi, 1973-; Gómez Gutiérrez, Emilia, 1975- (International Society for Music Information Retrieval (ISMIR), 2020)
    Choral singing is a widely practiced form of ensemble singing wherein a group of people sing simultaneously in polyphonic harmony. The most commonly practiced setting for choir ensembles consists of four parts; Soprano, ...
  • Multi-type outer product-based fusion of respiratory sounds for detecting COVID-19
    Mallol Ragolta, Adrià; Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975-; Schuller, Björn (International Speech Communication Association (ISCA), 2022)
    This work presents an outer product-based approach to fuse the embedded representations learnt from the spectrograms of cough, breath, and speech samples for the automatic detection of COVID-19. To extract deep learnt ...
  • Multiple F0 estimation in vocal ensembles using convolutional neural networks
    Cuesta, Helena; McFee, Brian; Gómez Gutiérrez, Emilia, 1975- (International Society for Music Information Retrieval (ISMIR), 2020)
    This paper addresses the extraction of multiple F0 values from polyphonic and a cappella vocal performances using convolutional neural networks (CNNs). We address the major challenges of ensemble singing, i.e., all melodic ...
  • Voice assignment in vocal quartets using deep learning models based on pitch salience
    Cuesta, Helena; Gómez Gutiérrez, Emilia, 1975- (Ubiquity Press, 2022)
    This paper deals with the automatic transcription of four-part, a cappella singing, audio performances. In particular, we exploit an existing, deep-learning based, multiple F0 estimation method and complement it with two ...

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