Paper Info
Title
A ROS framework for audio-based activity recognition.
Abstract
Research on robot perception mostly focuses on visual information analytics. Audio-based perception is mostly based on speech-related information. However, non-verbal information of the audio channel can be equally important in the perception procedure, or at least play a complementary role. This paper presents a framework for audio signal analysis that utilizes the ROS architectural principles. Details on the design and implementation issues of this workflow are described, while classification results are also presented in the context of two use-cases motivated by the task of medical monitoring. The proposed audio analysis framework is provided as an open-source library at github (https://github.com/tyiannak/AUROS).
Year
DOI
Venue
2016
10.1145/2910674.2935858
PETRA
Field
DocType
Citations 
Audio signal,Activity recognition,Computer science,Communication channel,Feature extraction,Audio analyzer,Human–computer interaction,Analytics,Workflow,Multimedia,Perception
Conference
0
PageRank 
References 
Authors
0.34
3
2
Name
Order
Citations
PageRank
Theodoros Giannakopoulos121926.52
Georgios Siantikos200.34