In order to enhance people’s ability to interact with their acoustic environments, hearing devices are common tools. However, it is difficult to evaluate the benefit of those tools or to measure acoustically challenging situations in natural environments. This paper proposes a way to measure the most important features of everyday acoustics environments by extracting a limited set of features while not compromising the privacy of partners and bystanders. The respective national laws on how to deal with audio privacy are very different among countries. The authors proposed using a smartphone as the source recorder but splitting the feature extraction into two phases: an initial feature processing in the smartphone and a later processing on a more powerful computer. For a given feature set, a statistical analysis shows comparable results from the extracted data when using either the original audio or the new privacy-aware extraction methods. A comparison shows that different scenarios result in separable features using the new extraction method.
Open
Access
Download Now (1.1 MB)
This paper is Open Access which means you can download it for free.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can
subscribe to this RSS feed.
Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.
