In auditory signal processing research, we are often interested in algorithms that modify audible sounds, for example to increase speech intelligibility. Oftentimes, it is interesting and sufficient in an experiment to process such sounds offline and play them back to participants at a later stage. This approach has the advantage of full control over all parameters including background noise. However, in many situations it would be beneficial to have a more direct approach, by being able to manipulate sounds in real time. Real time processing of environmental sounds means giving up on controlling all environmental parameters, but gaining highest possible ecological validity, that is to test the participant in unpredictable situations as they would face in real life. This approach is important for example for hearing aid noise reduction algorithms, where the wearers outside of the lab encounter unpredictable situations.
In a typical development cycle, an algorithms’ benefit must first be demonstrated in laboratory situations, before going real time. However, only when knowing the interaction between algorithm and participant in real live situations, the algorithm can be fully evaluated for it’s usefulness. In fact, most algorithms that have shown benefit in laboratory situations were either never evaluated in real time environments or failed to live up to their promise. However, in order to develop algorithms that have potential to be implemented in the next generation of auditory devices, they must be tested in all situations, but testing real time algorithms in real live situations is difficult for many reasons. Firstly, programming them is difficult, as the necessary programming skills are not the same as for offline programming. Secondly, it often requires specialised hardware that is suited and fast enough to do the processing.
For signal processing research it would be beneficial to have a platform that helps to bridge the development from existing offline algorithms to real time.
We present here a comprehensive solution: a platform that enables current users of matlab to quickly port their algorithms to real time. We provide an open library that can be used freely and that will grow in future. The algorithms can run on standard PC hardware or on special hardware when required. The platform is the result of a European Training network (www.icanhear.eu), and all seven network partners have contributed to the library. The software is distributed freely via soundsoftware.ac.uk, where the library as well as supporting documentation can be downloaded for free under a fair use licence.
The library is open, that is, everybody (who is registered on the web page) can add algorithms.