Definition-independent Formalization of Soundscapes: Towards a Formal Methodology
Not on the map. Why?
Abstract (arXiv)
Soundscapes have been studied by researchers from various disciplines, each with different perspectives, goals, approaches, and terminologies. Accordingly, depending on the field, the concept of a soundscape's components changes, consequently changing the basic definition. This results in complicating interdisciplinary communication and comparison of results. Especially when soundscape-unrelated research areas are involved. For this reason, we present a potential formalization that is independent of the underlying soundscape definition, with the goal of being able to capture the heterogeneous structure of the data as well as the different ideologies in one model. In an exemplary analysis of frequency correlation matrices for land use type detection as an alternative to features like MFCCs, we show a practical application of our presented formalization.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 9 of its 55 references that are in the map. First posted on arXiv 20 Oct 2023.
Builds on
9 of 55 references.
References · 9
- 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,527
- 2015Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classificationcited by 3,611
- 2015Fast R-CNNcited by 2,933
- 2016Context Encoders: Feature Learning by Inpaintingcited by 1,428
- 2015Generating Sentences from a Continuous Spacecited by 612
- 2016Towards K-means-friendly Spaces: Simultaneous Deep Learning and Clusteringcited by 237
- 2017Optimizing the Latent Space of Generative Networkscited by 157
- 2014Acoustic Scene Classificationcited by 26
- 2020Urban Sound Classification : striving towards a fair comparisoncited by 3
Built on by
Not cited yet.