Prof. Dr. Dr. Birger Kollmeier

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W30 3-313


Katja Warnken

+49 (0)441 798-3902

W30 3-312

Kirsten Scheel

+49 (0)441 798-3813

+49 (0)441 798-3902

W30 3-312

Anschrift (Postanschrift)

Medizinische Physik, Fakultät VI
Universität Oldenburg
26111 Oldenburg

Standort / Anreise

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Sound classification and SNR prediction

Sound classification and SNR prediction

Problem: Automatic classification of the acoustical situation, and fast prediction of the local signal-to-noise ratio (SNR)

Application: VAD for mobile communication, noise suppression for e.g. hearing instruments

Motivation: Humans can easily detect and classify different sound sources, e.g., distinguish between speech and noise. Which features in the acoustic waveform allow for such impressive skills?

Approach: Modeling neurophysiological findings on amplitude modulation processing in the auditory system of mammals yielding spectro-temporal feature patterns. Classification and SNR prediction with artificial neural networks.

Implementation: Narrow-band SNR estimation fed into Wiener Filter like noise reduction algorithm. No assumption about stationarity of the noise and no speech pause detection necessary.

Paper free to download

  • paper_final.dvi Tchorz, J., Kleinschmidt, M., and Kollmeier, B.: 'Noise suppression based on neurophysiologically motivated SNR estimation for robust speech recognition', Proceedings of NIPS 2000, in press 219 KB
(Stand: 09.02.2024)  | 
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