Title :
Capturing Spontaneous Conversation and Social Dynamics: A Privacy-Sensitive Data Collection Effort
Author :
Wyatt, D. ; Choudhury, Tonmoy ; Kautz, H.
Author_Institution :
Dept. of Comput. Sci., Washington Univ., Seattle, WA, USA
Abstract :
The UW dynamic social network study is an effort to automatically observe and model the creation and evolution of a social network formed through spontaneous face-to-face conversations. We have collected more than 4,400 hours of data that capture the real world interactions between 24 subjects over a period of 9 months. The data was recorded in completely unconstrained and natural conditions, but was collected in a manner that protects the privacy of both study participants and non-participants. Despite the privacy constraints, the data allows for many different types of inference that are in turn useful for studying the prosodic and paralinguistic features of truly spontaneous speech across many subjects and over an extended period of time. This paper describes the new challenges and opportunities presented in such a study, our data collection effort, the problems we encountered, and the resulting corpus.
Keywords :
data acquisition; speech intelligibility; UW dynamic social network; paralinguistic features; privacy constraints; privacy-sensitive data collection effort; prosodic features; social dynamics; spontaneous conversation; spontaneous face-to-face conversations; Audio recording; Computer science; Data privacy; Infrared sensors; Microphones; Personal digital assistants; Protection; Social network services; Speech; Temperature sensors; Data acquisition; oral communication; privacy; speech analysis;
Conference_Titel :
Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0727-3
DOI :
10.1109/ICASSP.2007.367201