TY - JOUR
T1 - Large-scale Data Collection and Analysis via a Gamified Intelligent Crowdsourcing Platform
AU - Hantke, Simone
AU - Olenyi, Tobias
AU - Hausner, Christoph
AU - Appel, Tobias
AU - Schuller, Björn
N1 - Publisher Copyright:
© 2019, Institute of Automation, Chinese Academy of Sciences and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2019/8/1
Y1 - 2019/8/1
N2 - In this contribution, we present iHEARu-PLAY, an online, multi-player platform for crowdsourced database collection and labelling, including the voice analysis application (VoiLA), a free web-based speech classification tool designed to educate iHEARu-PLAY users about state-of-the-art speech analysis paradigms. Via this associated speech analysis web interface, in addition, VoiLA encourages users to take an active role in improving the service by providing labelled speech data. The platform allows users to record and upload voice samples directly from their browser, which are then analysed in a state-of-the-art classification pipeline. A set of pre-trained models targeting a range of speaker states and traits such as gender, valence, arousal, dominance, and 24 different discrete emotions is employed. The analysis results are visualised in a way that they are easily interpretable by laymen, giving users unique insights into how their voice sounds. We assess the effectiveness of iHEARu-PLAY and its integrated VoiLA feature via a series of user evaluations which indicate that it is fun and easy to use, and that it provides accurate and informative results.
AB - In this contribution, we present iHEARu-PLAY, an online, multi-player platform for crowdsourced database collection and labelling, including the voice analysis application (VoiLA), a free web-based speech classification tool designed to educate iHEARu-PLAY users about state-of-the-art speech analysis paradigms. Via this associated speech analysis web interface, in addition, VoiLA encourages users to take an active role in improving the service by providing labelled speech data. The platform allows users to record and upload voice samples directly from their browser, which are then analysed in a state-of-the-art classification pipeline. A set of pre-trained models targeting a range of speaker states and traits such as gender, valence, arousal, dominance, and 24 different discrete emotions is employed. The analysis results are visualised in a way that they are easily interpretable by laymen, giving users unique insights into how their voice sounds. We assess the effectiveness of iHEARu-PLAY and its integrated VoiLA feature via a series of user evaluations which indicate that it is fun and easy to use, and that it provides accurate and informative results.
KW - Human computation
KW - crowdsourcing
KW - gamified data collection
KW - speech analysis
KW - survey
UR - http://www.scopus.com/inward/record.url?scp=85069475895&partnerID=8YFLogxK
U2 - 10.1007/s11633-019-1180-0
DO - 10.1007/s11633-019-1180-0
M3 - Article
AN - SCOPUS:85069475895
SN - 1476-8186
VL - 16
SP - 427
EP - 436
JO - International Journal of Automation and Computing
JF - International Journal of Automation and Computing
IS - 4
ER -