Paper Info
Title
Can a Mobile Phone in a Pocket Reliably Recognize Ambient Sounds?
Abstract
We investigate how different locations inside clothing influence the ability of a system to recognize activity relevant sounds. Specifically, we consider the recognition of sounds from 9 household and office appliances recorded using an iPhone placed in 2 trouser pockets, 2 jacket pockets, a belt holster and the users’ hand. The aim is not to demonstrate good recognition rates on the above sounds (which has been done many times before) but to compare recognition rates from the individual locations and to understand how to best train the system to be location invariant.
Year
DOI
Venue
2009
10.1109/ISWC.2009.34
ISWC
Keywords
Field
DocType
activity relevant sound,good recognition rate,different location,location invariant,pocket reliably recognize ambient,recognition rate,office appliance,mobile phone,belt holster,individual location,jacket pocket,clothing influence,clothing,training data,noise
Training set,Computer vision,Ambient noise level,Computer science,Clothing,Artificial intelligence,Mobile phone,Embedded system
Conference
ISSN
Citations 
PageRank 
1550-4816
8
0.63
References 
Authors
5
4
Name
Order
Citations
PageRank
Tobias Franke11148.02
Paul Lukowicz23287376.79
Kai Kunze3898126.25
David Bannach431927.65