Biblio

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2019
Blaauw, M., Bonada J., & Daido R. (2019).  Data Efficient Voice Cloning for Neural Singing Synthesis. 2019 IEEE International Conference on Acoustics, Speech and Signal Processing.
Slizovskaia, O., Kim L., Haro G., & Gómez E. (2019).  End-to-End Sound Source Separation Conditioned On Instrument Labels. 2019 International Conference on Acoustics, Speech, and Signal Processing. Abstract
Fonseca, E., Plakal M., Ellis D. P. W., Font F., Favory X., & Serra X. (2019).  Learning Sound Event Classifiers from Web Audio with Noisy Labels. International Conference on Acoustics, Speech and Signal Processing (ICASSP). Abstract
Chandna, P., Blaauw M., Bonada J., & Gomez E. (2019).  A Vocoder Based Method For Singing Voice Extraction. 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2019). Abstract
Porcaro, L., & Saggion H. (2019).  Recognizing Musical Entities in User-generated Content. International Conference on Computational Linguistics and Intelligent Text Processing (CICLing) 2019. Abstract
Pons, J., & Serra X. (2019).  Randomly weighted CNNs for (music) audio classification. 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2019). Abstract
Pons, J., Serrà J., & Serra X. (2019).  Training neural audio classifiers with few data. 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP2019). Abstract
2018
Caro Repetto, R., Pretto N., Chaachoo A., Bozkurt B., & Serra X. (2018).  An open corpus for the computational research of Arab-Andalusian music. 5th International Conference on Digital Libraries for Musicology (DLfM 2018). 78-86. Abstract
Fernández-Macías, E., Gomez E., Hernández-Orallo J., Loe B. - S., Martens B., Martínez-Plumed F., et al. (2018).  A multidisciplinary task-based perspective for evaluating the impact of AI autonomy and generality on the future of work. Workshop on architectures and evaluation for generality, autonomy and progress in AI, IJCAI-ECAI 2018, AAMAS 2018 AND ICML 2018.
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.
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