Name
Title | ||
|---|---|---|
Type/position classification of inter-floor noise in residential buildings with a single microphone via supervised learning |
Abstract | ||
|---|---|---|
Inter-floor noise propagates through a building structure from a noise source to neighbors on other floors. Identification of type/position of inter-floor noise in a building is difficult for human hearing. A convolutional neural network-based inter-floor noise type/position classification method was proposed in [Appl. Sci. 9, 3735 (2019)] to identify inter-floor noise. The method was evaluated against inter-floor noise collected in a single campus building as a feasibility test. In this work, the generalizability of the method was addressed through numerous tasks using new datasets collected in two real apartment buildings. These datasets contain inter-floor noise generated in rooms and at positions with three-dimensional spatial diversity, which was not studied in the previous work. Furthermore, type classification knowledge transfer between two individual apartment building domains was studied. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.23919/Eusipco47968.2020.9287868 | 2020 28th European Signal Processing Conference (EUSIPCO) |
Keywords | DocType | ISSN |
Inter-floor noise,single sensor acoustics,convolutional neural network,knowledge transfer | Conference | 2219-5491 |
ISBN | Citations | PageRank |
978-1-7281-5001-7 | 0 | 0.34 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hwiyong Choi | 1 | 0 | 0.68 |
| Haesang Yang | 2 | 0 | 0.34 |
| Seung Jun Lee | 3 | 16 | 8.23 |
| Woojae Seong | 4 | 1 | 2.74 |