Cobos, M., Antonacci, F., Comanducci, L., & Sarti, A. (2020). Frequency-sliding generalized cross-correlation: a sub-band time delay estimation approach. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28, 1270-1281. https://doi.org/10.1109/TASLP.2020.2983589
Belloch, J. A., Badía, J. M., Igual, F. D., & Cobos, M. (2019). Practical considerations for acoustic source localization in the IoT era: Platforms, energy efficiency, and performance. IEEE Internet of Things Journal, 6(3), 5068-5079.https://doi.org/10.1109/JIOT.2019.2895742
Fabregat, G., Belloch, J. A., Badía, J. M., & Cobos, M. (2020). Design and implementation of acoustic source localization on a low-cost IoT edge platform. IEEE Transactions on Circuits and Systems II: Express Briefs, 67(12), 3547-3551.https://doi.org/10.1109/TCSII.2020.2986296
Badía, J. M., Belloch, J. A., Cobos, M., Igual, F. D., & Quintana-Ortí, E. S. (2019). Accelerating the SRP-PHAT algorithm on multi-and many-core platforms using OpenCL. The Journal of Supercomputing, 75(3), 1284-1297.https://doi.org/10.1007/s11227-018-2422-6
Martín-Morató, I., Cobos, M., & Ferri, F. J. (2020). Adaptive Distance-Based Pooling in Convolutional Neural Networks for Audio Event Classification. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 28, 1925-1935.https://doi.org/10.1109/TASLP.2020.3001683
Naranjo-Alcazar, J., Perez-Castanos, S., Martín-Morató, I., Zuccarello, P., Ferri, F. J., & Cobos, M. (2020). A Comparative Analysis of Residual Block Alternatives for End-to-End Audio Classification. IEEE Access, 8, 188875-188882.https://doi.org/10.1109/ACCESS.2020.3031685
Naranjo-Alcazar, J., Perez-Castanos, S., Zuccarello, P., & Cobos, M. (2020). Acoustic scene classification with squeeze-excitation residual networks. IEEE Access, 8, 112287-112296.https://doi.org/10.1109/ACCESS.2020.3002761
Naranjo-Alcazar, J., Perez-Castanos, S., Zuccarello, P., Antonacci, F., & Cobos, M. (2020). Open set audio classification using autoencoders trained on few data. Sensors, 20(13), 3741.https://doi.org/10.3390/s20133741
Lopez-Ballester, J., Pastor-Aparicio, A., Felici-Castell, S., Segura-Garcia, J., & Cobos, M. (2020). Enabling Real-Time Computation of Psycho-acoustic Parameters in Acoustic Sensors Using Convolutional Neural Networks. IEEE Sensors Journal, 20(19), 11429-11438.https://doi.org/10.1109/JSEN.2020.2995779
Pastor-Aparicio, A., Segura-Garcia, J., Lopez-Ballester, J., Felici-Castell, S., García-Pineda, M., & Pérez-Solano, J. J. (2019). Psychoacoustic Annoyance Implementation With Wireless Acoustic Sensor Networks for Monitoring in Smart Cities. IEEE Internet of Things Journal, 7(1), 128-136.https://doi.org/10.1109/JIOT.2019.2946971
Lopez-Ballester, J., Pastor-Aparicio, A., Segura-Garcia, J., Felici-Castell, S., & Cobos, M. (2019). Computation of psycho-acoustic annoyance using deep neural networks. Applied Sciences, 9(15), 3136.https://doi.org/10.3390/app9153136
Belloch, J. A., Ramos, G., Badia, J. M., & Cobos, M. (2020). An efficient implementation of parallel parametric HRTF models for binaural sound synthesis in mobile multimedia. IEEE Access, 8, 49562-49573.https://doi.org/10.1109/ACCESS.2020.2979489
Cobos, M., & Roger, S. (2019). SART3D: A MATLAB toolbox for spatial audio and signal processing education. Computer Applications in Engineering Education, 27(4), 971-985.https://doi.org/10.1002/cae.7
Arevalillo-Herráez, M., Cobos, M., Roger, S., & García-Pineda, M. (2019). Combining inter-subject modeling with a subject-based data transformation to improve affect recognition from EEG signals. Sensors, 19(13), 2999.https://doi.org/10.3390%2Fs19132999
Nguyen, B., Ferri, F. J., Morell, C., & De Baets, B. (2019). An efficient method for clustered multi-metric learning. Information Sciences, 471, 149-163. https://doi.org/10.1016/j.ins.2018.08.055
Fayos-Jordan, R., Felici-Castell, S., Segura-Garcia, J., Lopez-Ballester, J., & Cobos, M. (2020). Performance comparison of container orchestration platforms with low cost devices in the fog, assisting Internet of Things applications. Journal of Network and Computer Applications, 169, 102788.https://doi.org/10.1016/j.jnca.2020.102788
Pezzoli, M., Carabias-Orti, J. J., Cobos, M., Antonacci, F., & Sarti, A. (2021). Ray-space-based multichannel nonnegative matrix factorization for audio source separation. IEEE Signal Processing Letters, 28, 369-373.https://doi.org/10.1109/LSP.2021.3055463
Lopez-Ballester, J., Alcaraz Calero, J. M., Segura-Garcia, J., Felici-Castell, S., Garcia-Pineda, M., & Cobos, M. (2021). Speech intelligibility analysis and approximation to room parameters through the Internet of Things. Applied Sciences, 11(4), 1430.https://doi.org/10.3390/app11041430
Lopez, J. J., Gutierrez-Parera, P., & Cobos, M. (2022). Compensating first reflections in non-anechoic head-related transfer function measurements. Applied Acoustics, 188, 108523.https://doi.org/10.1016/j.apacoust.2021.108523
Naranjo-Alcazar, J., Perez-Castanos, S., Zuccarello, P., Torres, A. M., Lopez, J. J., Ferri, F. J., & Cobos, M. (2022). An open-set recognition and few-shot learning dataset for audio event classification in domestic environments. Pattern Recognition Letters, 164, 40-45.https://doi.org/10.1016/j.patrec.2022.10.019
Cobos, M., Ahrens, J., Kowalczyk, K., & Politis, A. (2022). An overview of machine learning and other data-based methods for spatial audio capture, processing, and reproduction. EURASIP Journal on Audio, Speech, and Music Processing, 2022(1), 1-21.http://dx.doi.org/10.1186/s13636-022-00242-x
Cobos, M., Ahrens, J., Kowalczyk, K., & Politis, A. (2022). Data-based spatial audio processing. EURASIP Journal on Audio, Speech, and Music Processing, 2022(1), 1-3.https://doi.org/10.1186/s13636-022-00248-5
Lopez-Ballester, J., Felici-Castell, S., Segura-Garcia, J., & Cobos, M. (2022). AI-IoT Platform for Blind Estimation of Room Acoustic Parameters Based on Deep Neural Networks. IEEE Internet of Things Journal, 10(1), 855-866.https://doi.org/10.1109/JIOT.2022.3203570