Kolloquium - Details zum Vortrag
Sie werden über Vorträge rechtzeitig per E-Mail informiert werden, wenn Sie den Newsletter des kommunikationstechnischen Kolloquiums abonnieren.
Alle Interessierten sind herzlich eingeladen, eine Anmeldung ist nicht erforderlich.
Promotions-Vortrag: Speech Signal Enhancement by Information Combining
Dipl.-Ing. Florian Heese
22. September 2016
10:30 Uhr
Hörsaal 4G IKS
Nowadays audio- communication takes place using mobile phones, tablets or hearing aids at different locations and in a large variety of acoustic environments. The intelligibility as well as the quality of speech may significantly degrade by ambient background noise. In order to improve the speech intelligibility and to ensure a convenient communication with high audio quality, speech enhancement techniques are required. In this thesis all critical components for enhancing the up-link signal are addressed:
- the capturing at the acoustic front-end via a new near field beamformer,
- a new codebook based speech and noise estimation procedure generating and exploiting reliability information,and
- noise reduction exploiting spectral dependencies of human speech.
For the acoustic front-end of the digital processing chain a novel concept for the filter optimization of a near field beamformer is introduced. The optimization scheme allows to closely approximate a predefined reception characteristic which can be freely chosen according to the application. The output of the beamformer provides an optimized SNR at the acoustic front-end and a pre-enhanced signal for a subsequent single-sensor based speech enhancement system.
Single channel noise reduction usually relies on statistical properties of speech and noise for signal enhancement. In general, the noise is assumed to be stationary or only slightly time-varying, which is in practice often not fulfilled. Due to imprecise noise estimation, single-sensor systems are prone to unpleasant artifacts that are called musical tones. In this context different Information Combining methods are presented which address specifically the problematic of non-stationary noise signals, leading to a significant improved estimation accuracy.
On the one hand, the proposed Information Combining is used with respect to spectral correlation of human speech. On the other hand, it merges the best of several speech and noise estimates depending on their reliability. The necessary estimates are provided by a new statistical based noise estimator as well as a codebook driven speech and noise estimation system. The achieved quality closes the gap between the conflicting goals of high noise attenuation, low speech distortion, and the prevention of undesired musical tone artifacts. Finally, the practical aspects of the proposed enhancement systems are considered and discussed with two implemented real-time demonstrators.
