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ORCIDIrene Martín-Morató
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- affiliation: Tampere University, Computing Sciences, Finland
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2020 – today
- 2024
[i3]Florian Schmid, Paul Primus, Toni Heittola, Annamaria Mesaros, Irene Martín-Morató, Khaled Koutini, Gerhard Widmer:
Data-Efficient Low-Complexity Acoustic Scene Classification in the DCASE 2024 Challenge. CoRR abs/2405.10018 (2024)- 2023
- [j4]Irene Martín-Morató
, Annamaria Mesaros:
Strong Labeling of Sound Events Using Crowdsourced Weak Labels and Annotator Competence Estimation. IEEE ACM Trans. Audio Speech Lang. Process. 31: 902-914 (2023) - [c10]Irene Martín-Morató, Manu Harju, Paul Ahokas, Annamaria Mesaros:
Training Sound Event Detection with Soft Labels from Crowdsourced Annotations. ICASSP 2023: 1-5 - [i2]Irene Martín-Morató, Manu Harju, Paul Ahokas, Annamaria Mesaros:
Training sound event detection with soft labels from crowdsourced annotations. CoRR abs/2302.14572 (2023) - 2022
- [c9]Irene Martín-Morató, Manu Harju, Annamaria Mesaros:
A Summarization Approach to Evaluating Audio Captioning. DCASE 2022 - [c8]Irene Martín-Morató, Francesco Paissan, Alberto Ancilotto, Toni Heittola, Annamaria Mesaros, Elisabetta Farella, Alessio Brutti, Tuomas Virtanen:
Low-Complexity Acoustic Scene Classification in DCASE 2022 Challenge. DCASE 2022 - 2021
- [c7]Irene Martín-Morató, Toni Heittola, Annamaria Mesaros, Tuomas Virtanen:
Low-Complexity Acoustic Scene Classification for Multi-Device Audio: Analysis of DCASE 2021 Challenge Systems. DCASE 2021: 85-89 - [c6]Irene Martín-Morató, Annamaria Mesaros:
Diversity and Bias in Audio Captioning Datasets. DCASE 2021: 90-94 - [c5]Irene Martín-Morató, Annamaria Mesaros:
What is the ground truth? Reliability of multi-annotator data for audio tagging. EUSIPCO 2021: 76-80 - [c4]Irene Martín-Morató, Manu Harju, Annamaria Mesaros:
Crowdsourcing Strong Labels for Sound Event Detection. WASPAA 2021: 246-250 - 2020
- [j3]Javier Naranjo-Alcazar, Sergi Perez-Castanos, Irene Martín-Morató, Pedro Zuccarello, Francesc J. Ferri, Maximo Cobos:
A Comparative Analysis of Residual Block Alternatives for End-to-End Audio Classification. IEEE Access 8: 188875-188882 (2020) - [j2]Irene Martín-Morató, Maximo Cobos, Francesc J. Ferri:
Adaptive Distance-Based Pooling in Convolutional Neural Networks for Audio Event Classification. IEEE ACM Trans. Audio Speech Lang. Process. 28: 1925-1935 (2020)
2010 – 2019
- 2019
- [c3]Irene Martín-Morató, Annamaria Mesaros, Toni Heittola, Tuomas Virtanen, Maximo Cobos, Francesc J. Ferri:
Sound Event Envelope Estimation in Polyphonic Mixtures. ICASSP 2019: 935-939 - [i1]Javier Naranjo-Alcazar, Sergi Perez-Castanos, Irene Martín-Morató, Pedro Zuccarello, Maximo Cobos:
On the performance of residual block design alternatives in convolutional neural networks for end-to-end audio classification. CoRR abs/1906.10891 (2019) - 2018
- [j1]Irene Martín-Morató, Maximo Cobos, Francesc J. Ferri:
Adaptive Mid-Term Representations for Robust Audio Event Classification. IEEE ACM Trans. Audio Speech Lang. Process. 26(12): 2381-2392 (2018) - 2017
- [c2]Irene Martín-Morató, Maximo Cobos, Francesc J. Ferri:
Analysis of data fusion techniques for multi-microphone audio event detection in adverse environments. MMSP 2017: 1-6 - 2016
- [c1]Irene Martín-Morató, Maximo Cobos, Francesc J. Ferri:
A case study on feature sensitivity for audio event classification using support vector machines. MLSP 2016: 1-6
Coauthor Index
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last updated on 2024-06-25 20:57 CEST by the dblp team
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