Digital Enhancement of Speech Perception in Noisy Environments

The perception of loudspeaker speech
from public address systems or mobile phones is often affected by local
background noise. In order to improve the speech intelligibility,
“Near-End Listening Enhancement” (NELE) can be applied. This processing
adaptively modifies the loudspeaker signal by taking the instantaneous
background noise into account. The main novel contributions of this
thesis are NELE frequency domain weighting rules without need for
complex optimization and NELE time domain filter structures with low
latency and complexity. Furthermore, NELE solutions for public address
systems with massive crosstalk, such as railway stations, are presented.
In addition, solutions for combined operation of NELE with far-end
noise reduction are developed, which are relevant for mobile telephony.
Listening tests as well as objective measures confirm a significant
increase in intelligibility.