7200 .csv files, each containing a 10 kHz recording of a 1 ms lasting 100 hz sound, recorded centimeterwise in a 20 cm x 60 cm locating range on a table. 3600 files (3 at each of the 1200 different positions) are without an obstacle between the loudspeaker and the microphone, 3600 RIR recordings are affected by the changes of the object (a book). The OOLA is initially trained offline in batch mode by the first instance of the RIR recordings without the book. Then it learns online in an incremental mode how the RIR changes by the book.

Dataset Files

You must be an IEEE Dataport Subscriber to access these files. Subscribe now or login.

[1] Rüdiger Machhamer, "Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data", IEEE Dataport, 2019. [Online]. Available: http://dx.doi.org/10.21227/j59n-p811. Accessed: Oct. 12, 2024.
@data{j59n-p811-19,
doi = {10.21227/j59n-p811},
url = {http://dx.doi.org/10.21227/j59n-p811},
author = {Rüdiger Machhamer },
publisher = {IEEE Dataport},
title = {Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data},
year = {2019} }
TY - DATA
T1 - Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data
AU - Rüdiger Machhamer
PY - 2019
PB - IEEE Dataport
UR - 10.21227/j59n-p811
ER -
Rüdiger Machhamer. (2019). Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data. IEEE Dataport. http://dx.doi.org/10.21227/j59n-p811
Rüdiger Machhamer, 2019. Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data. Available at: http://dx.doi.org/10.21227/j59n-p811.
Rüdiger Machhamer. (2019). "Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data." Web.
1. Rüdiger Machhamer. Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data [Internet]. IEEE Dataport; 2019. Available from : http://dx.doi.org/10.21227/j59n-p811
Rüdiger Machhamer. "Online Offline Learning for Sound-based Indoor Localization Using Low-cost Hardware Data." doi: 10.21227/j59n-p811