Prof-Life-Log: Personal interaction analysis for naturalistic audio streams

Analysis of personal audio recordings is a challenging and interesting subject. Using contemporary speech and language processing techniques, it is possible to mine personal audio recordings for a wealth of information that can be used to measure a person´s engagement with their environment as well as other people. In this study, we propose an analysis system that uses personal audio recordings to automatically estimate the number of unique people and environments which encompass the total engagement within the recording. The proposed system uses speech activity detection (SAD), speaker diarization and environmental sniffing techniques, and is evaluated on naturalistic audio streams from the Prof-Life-Log corpus. We also report performance of the individual systems, and also present a combined analysis which reveals the interaction of the subject with both people and environment. Hence, this study establishes the efficacy and novelty of using contemporary speech technology for life logging applications.