Final published version
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Voice Äpp
T2 - a mobile app for crowdsourcing Swiss German dialect data
AU - Leemann, Adrian
AU - Kolly, Marie-José
AU - Goldman, Jean-Philippe
AU - Dellwo, Volker
AU - Hove, Ingrid
AU - Almajai, Ibrahim
AU - Grimm, Sarah
AU - Robert, Sylvain
AU - Wanitsch, Daniel
PY - 2015
Y1 - 2015
N2 - Crowdsourcing speech data through mobile applications is relatively new. In the present contribution we add to the existing body of research an innovative Android and iOS application called `Voice Äpp'. The free app is pioneering in the sense that it leverages its function as a medium for science communication — thus attracting an extensive user base — to crowdsource audio and dialect data. The app was launched in early 2015 and has already been downloaded 19k times. Nearly half a million audio tokens have been crowdsourced. In this system levels contribution we describe the basic functionalities of the app — voice and dialect analysis —, we present the scientific potential of the corpus created, and discuss methodological issues related to crowdsourcing audio data through mobile applications.
AB - Crowdsourcing speech data through mobile applications is relatively new. In the present contribution we add to the existing body of research an innovative Android and iOS application called `Voice Äpp'. The free app is pioneering in the sense that it leverages its function as a medium for science communication — thus attracting an extensive user base — to crowdsource audio and dialect data. The app was launched in early 2015 and has already been downloaded 19k times. Nearly half a million audio tokens have been crowdsourced. In this system levels contribution we describe the basic functionalities of the app — voice and dialect analysis —, we present the scientific potential of the corpus created, and discuss methodological issues related to crowdsourcing audio data through mobile applications.
M3 - Conference contribution/Paper
T3 - Proceedings of Interspeech
SP - 2804
EP - 2808
BT - Interspeech 2015
ER -