Quality Assessment of Speech Enhanced using Particle Filters
Frédéric Mustière, Martin Bouchard, Miodrag Bolić · 2007
Among the various types of existing speech enhancement algorithms, respective advantages are usually well-known and well-studied, making it possible to choose the right algorithm given a certain type of audio quality requirement (e.g. background noise intrusiveness, naturalness of the speech, etc.). Very little has however been said so far on the quality of speech enhanced by particle filters (PFs). In this paper, we show the detailed results of the analysis of PF-enhanced speech signals. This analysis is conducted using several objective measures, and is based on the comparison with other enhancement algorithms. We find that in general, PF-based algorithms yield speech signals which are among the most natural-sounding, with a residual noise that can be seen as a white noise with its variance "modulated" by the resulting speech.