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Access to informative databases is a crucial part of notable researchdevelopments. In the field of domestic audio classification, there have beensignificant advances in recent years. Although several audio databases exist,these can be limited in terms of the amount of information they provide, suchas the exact location of the sound sources, and the associated noise levels. Inthis work, we detail our approach on generating an unbiased synthetic domesticaudio database, consisting of sound scenes and events, emulated in both quietand noisy environments. Data is carefully curated such that it reflects issuescommonly faced in a dementia patients environment, and recreate scenarios thatcould occur in real-world settings. Similarly, the room impulse responsegenerated is based on a typical one-bedroom apartment at Hebrew SeniorLifeFacility. As a result, we present an 11-class database containing excerpts ofclean and noisy signals at 5-seconds duration each, uniformly sampled at 16kHz. Using our baseline model using Continues Wavelet Transform Scalograms andAlexNet, this yielded a weighted F1-score of 86.24 percent.

DASEE A Synthetic Database of Domestic Acoustic Scenes and Events in Dementia Patients Environment