Kuvaus
The two .zip files contain the pre-trained weights, features, and labels for the AUDASC. In order to use them, you need the code of AUDASC (available from here). The code of AUDASC is based on PyTorch framework. For easy and efficient reproducibility, we include our extracted features and labels (one-hot encoded) from the development dataset of the DCASE 2018 Task 1, subtask B. The license specified by the DCASE 2018 Task1, subtask B, for the data is applied here to the extracted features and labels as well.
| Koska saatavilla | 22 elok. 2018 |
|---|---|
| Julkaisija | Zenodo |
Field of science, Statistics Finland
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Tutkimustuotos
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Unsupervised Adversarial Domain Adaptation for Acoustic Scene Classification
Gharib, S., Drossos, K., Cakir, E., Serdyuk, D. & Virtanen, T., 2018, Proceedings of the Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE2018). Tampere University of TechnologyTutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu
Open access
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