Near end listening enhancement optimized with respect to speech intelligibility index and audio power limitations

In speech communications, signal processing algorithms for near end listening enhancement allow to improve the intelligibility of clean (far end) speech for the near end listener who perceives not only the far end speech but also ambient background noise. A typical scenario is mobile telephony in acoustical background noise such as traffic or babble noise. In these situations, it is often not acceptable/possible to increase the audio power amplification. In this contribution we use a theoretical analysis of the Speech Intelligibility Index (SII) to develop an algorithm which numerically maximizes the SII under the constraint of an unchanged average power of the audio signal.