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Helena Cuesta
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- affiliation: Pompeu Fabra University, Barcelona, Spain
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2020 – today
- 2023
- [c6]Helena Cuesta, Nadine Kroher, Aggelos Pikrakis, Stojan Djordjevic:
DAACI-VoDAn: Improving Vocal Detection with New Data and Methods. EUSIPCO 2023: 136-140 - [i8]Nadine Kroher, Helena Cuesta, Aggelos Pikrakis:
Can MusicGen Create Training Data for MIR Tasks? CoRR abs/2311.09094 (2023) - 2022
- [b1]Helena Cuesta:
Data-driven pitch content description of choral singing recordings. Pompeu Fabra University, Spain, 2022 - [j2]Helena Cuesta, Emilia Gómez:
Voice Assignment in Vocal Quartets Using Deep Learning Models Based on Pitch Salience. Trans. Int. Soc. Music. Inf. Retr. 5(1): 99 (2022) - [c5]Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez, Björn W. Schuller:
Multi-Type Outer Product-Based Fusion of Respiratory Sounds for Detecting COVID-19. INTERSPEECH 2022: 2163-2167 - 2021
- [c4]Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez, Björn W. Schuller:
Cough-Based COVID-19 Detection with Contextual Attention Convolutional Neural Networks and Gender Information. Interspeech 2021: 941-945 - [i7]Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez, Björn W. Schuller:
EIHW-MTG DiCOVA 2021 Challenge System Report. CoRR abs/2110.06543 (2021) - [i6]Adria Mallol-Ragolta, Helena Cuesta, Emilia Gómez, Björn W. Schuller:
EIHW-MTG: Second DiCOVA Challenge System Report. CoRR abs/2110.09239 (2021) - 2020
- [j1]Sebastian Rosenzweig
, Helena Cuesta, Christof Weiß
, Frank Scherbaum, Emilia Gómez, Meinard Müller:
Dagstuhl ChoirSet: A Multitrack Dataset for MIR Research on Choral Singing. Trans. Int. Soc. Music. Inf. Retr. 3(1): 98-110 (2020) - [c3]Helena Cuesta, Brian McFee, Emilia Gómez:
Multiple F0 Estimation in Vocal Ensembles using Convolutional Neural Networks. ISMIR 2020: 302-309 - [c2]Pritish Chandna, Helena Cuesta, Emilia Gómez:
A Deep Learning Based Analysis-Synthesis Framework For Unison Singing. ISMIR 2020: 598-604 - [c1]Darius Petermann, Pritish Chandna, Helena Cuesta, Jordi Bonada, Emilia Gómez:
Deep Learning Based Source Separation Applied To Choir Ensembles. ISMIR 2020: 733-739 - [i5]Darius Petermann, Pritish Chandna, Helena Cuesta, Jordi Bonada, Emilia Gómez:
Deep Learning Based Source Separation Applied To Choir Ensembles. CoRR abs/2008.07645 (2020) - [i4]Helena Cuesta, Brian McFee, Emilia Gómez:
Multiple F0 Estimation in Vocal Ensembles using Convolutional Neural Networks. CoRR abs/2009.04172 (2020) - [i3]Pritish Chandna, Helena Cuesta, Emilia Gómez:
A Deep Learning Based Analysis-Synthesis Framework For Unison Singing. CoRR abs/2009.09875 (2020)
2010 – 2019
- 2019
- [i2]Helena Cuesta, Emilia Gómez, Pritish Chandna:
A Framework for Multi-f0 Modeling in SATB Choir Recordings. CoRR abs/1904.05086 (2019) - 2018
- [i1]Emilia Gómez, Merlijn Blaauw, Jordi Bonada, Pritish Chandna, Helena Cuesta:
Deep Learning for Singing Processing: Achievements, Challenges and Impact on Singers and Listeners. CoRR abs/1807.03046 (2018)
Coauthor Index
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