Applied Methods for Blind Speech Enhancement
|Title:||Applied Methods for Blind Speech Enhancement|
|Series:||Blekinge Institute of Technology Doctoral Dissertation Series|
|Publisher:||Blekinge Institute of Technology|
|Organization:||Blekinge Institute of Technology|
|Department:||School of Engineering - Dept. of Signal Processing (Sektionen för teknik – avd. för signalbehandling)
School of Engineering S- 372 25 Ronneby
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|Abstract:||Acoustic disturbances influence human speech communication by interfering with the communication process. In the worst case, it is impossible to communicate at all due to these disturbances. Methods that reduce the influence of the disturbances while preserving speech intelligibility are often desired. This thesis proposes real-world solutions for applied speech enhancement using autonomous and robust methods. Most of the work of the thesis concerns solutions to the problem of reducing acoustic disturbances within the framework of Blind Speech Enhancement (BSE). Notably, the term "blind" is assigned a positive attribute as it implies that the speech enhancement is carried out without any explicit references required. Instead, an assumption about the statistical independence between the sources coupled with an assumption regarding distinguishing statistical properties of the sources underpin the proposed methods. The unifying theory is Independent Component Analysis (ICA), which is performed by means of spatial filtering.
Two of the methods that are proposed in this thesis are shown, both in a theoretical and an empirical framework, to be robust in a real application while preserving stability even for Gaussianonly sources. Existing methods cannot guarantee stability in this scenario and Gaussian-only source mixtures may be the case in a real environment. The difference between the two methods lies in the different optimization strategies and the introduced approximations. The idea of injecting a single-channel method into the control loop of a blind beamformer is also proposed. In particular, two approaches are derived that aim at improving the blind beamformer in the case of disturbing noise and maintaining the same performance for different signal input levels. Finally, implementation aspects of a single-channel speech enhancer are discussed. The implementation aspects deal with the implementation of a speech enhancer in several different platforms such as analogue hardware, digital hardware, as well as hybrid analogue and digital hardware.
|Subject:||Signal Processing\Speech Enhancement|