Mobile telephony is often conducted in the presence of acoustical background noise such as traffic or babble noise. In this situation, the near-end listener perceives a mixture of clean far-end (downlink) speech and environmental noise from the near-end side, which goes along with an increased listening effort and possibly reduced speech intelligibility. As in many cases the noise signal cannot be influenced, the manipulation of the far-end signal is the only way to effectively improve speech intelligibility and to ease listening effort for the near-end listener by digital signal processing. We call this approach near-end listening enhancement (NELE).
In this thesis, innovative solutions for the problem of near-end listening enhancement are developed. These optimize the intelligibility of the far-end speech in local background noise with respect to the objective criterion Speech Intelligibility Index (SII). In contrast to state-of-the-art techniques, the developed methods tackle the problem for the first time from the application perspective considering also the requirements and restrictions of realistic scenarios such as in mobile phones. It is of particular importance that the processing adapts dynamically to the sound characteristics of the ambient noise. Hence, an effective intelligibility enhancement is provided in the presence of background noise, while in silence no audible modification is applied. The utilized noise tracking algorithm estimates the noise spectrum blindly from the microphone signal, the only access to the acoustical environment. Furthermore, a power limitation in critical bands ensures that the ear of the near-end listener is protected from damage and pain.