Evaluating BSS Algorithms in a Mobile Context Realized by a Client-Server Architecture

The human daily and the professional life demand a high amount of communication ability, but every fourth adult above 50 is hearing-impaired, a fraction that steadily increases in an aging society. For an autonomous, self-confident and long productive life, a good speech understanding in everyday life situations is necessary to reduce the listening effort. For this purpose, a mobile app-based assistance system based on Blind Source Separation is required that makes every-day acoustic scenarios more transparent by the opportunity of an interactive focusing on the preferred sound source in as close to real-time as possible. In case of highly costly BSS algorithms, at least an offline separation is to be provided. Developing such an app in the context of a short-term research project with limited budget to realize this goal statement makes it impossible to meet the challenge as a stand-alone solution with existing technologies and hardware. As an alternative, employing part of the required soft- and/or hardware on a remote server at least maintains the mobile context, given sufficient connectivity. For this purpose, a client-server architecture that combines Android, Java, MatlabControl and MATLAB, and that conducts separation of live recorded audio data remotely, is explained and tested. Conclusions about what is possible for the offline case are drawn from that. Tests are evaluated using a set of objective and subjective criteria. This demonstrates the possibility of realizing the assistance system in a mobile context.