Conference paper Open Access

A ROS Framework for Audio-Based Activity Recognition

Theodoros Giannakopoulos; Georgios Siantikos

JSON-LD ( Export

  "description": "<p>Research on robot perception mostly focuses on visual information analytics. Audio-based perception is mostly based<br>\non speech-related information. However, non-verbal information of the audio channel can be equally important in\u00a0the perception procedure, or at least play a complementary role. This paper presents a framework for audio signal\u00a0analysis that utilizes the ROS architectural principles. Details on the design and implementation issues of this workflow are described,\u00a0while classification results are\u00a0also presented in the context of two use-cases motivated by the\u00a0task of medical monitoring. The proposed\u00a0audio\u00a0analysis\u00a0framework is provided as an open-source\u00a0library at github\u00a0(</p>", 
  "license": "", 
  "creator": [
      "affiliation": "NCSR Demokritos", 
      "@type": "Person", 
      "name": "Theodoros Giannakopoulos"
      "affiliation": "NCSR Demokritos", 
      "@type": "Person", 
      "name": "Georgios Siantikos"
  "headline": "A ROS Framework for Audio-Based Activity Recognition", 
  "image": "", 
  "datePublished": "2016-07-01", 
  "url": "", 
  "@type": "ScholarlyArticle", 
  "keywords": [
    "audio analysis", 
    "audio segmentation", 
    "audio classification"
  "@context": "", 
  "identifier": "", 
  "@id": "", 
  "workFeatured": {
    "alternateName": "PETRA 2016", 
    "@type": "Event", 
    "name": "9th ACM International Conference on PErvasive Technologies Related to Assistive Environments"
  "name": "A ROS Framework for Audio-Based Activity Recognition"
Views 157
Downloads 374
Data volume 161.5 MB
Unique views 146
Unique downloads 358


Cite as