Frequency-Domain Processors for Efficient Removal of Noise and Unwanted Audio Events

Hatje U, Musialik CM. Frequency-Domain Processors for Efficient Removal of Noise and Unwanted Audio Events. In: AES Conference: 26th International Conference: Audio Forensics in the Digital Age. Audio Engineering Society; 2005. Paper 3-2. Available from: https://aes.org/publications/elibrary-page/?id=13243

@inproceedings{Hatje2005_13243,
  author = {Hatje, Ulrich and Musialik, Christoph M.},
  title = {{Frequency-Domain Processors for Efficient Removal of Noise and Unwanted Audio Events}},
  booktitle = {AES Conference: 26th International Conference: Audio Forensics in the Digital Age},
  note = {Paper 3-2},
  year = {2005},
  month = jul,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=13243}
}

TY  - CPAPER
TI  - Frequency-Domain Processors for Efficient Removal of Noise and Unwanted Audio Events
AU  - Hatje, Ulrich
AU  - Musialik, Christoph M.
T2  - AES Conference: 26th International Conference: Audio Forensics in the Digital Age
M1  - Paper 3-2
PY  - 2005
DA  - 2005/07/06
UR  - https://aes.org/publications/elibrary-page/?id=13243
PB  - Audio Engineering Society
LA  - en
AB  - Filtering heavily polluted audio signals with low-cut, high-cut or notch filters helps only if the spectrum of disturbances does not overlap the desired signal. Unfortunately, this is rarely the case in real situations. Therefore using frequencydomain methods is the only way to achieve dramatic improvements when cleaning up noisy signals. Spectral denoising works well in the case of broadband, smoothly changing noise, however, the situation become hopeless when the noise character changes abruptly and the S/N ratio is around zero decibels. We present a unique tool, reNOVAtor, working in 3D domain (time, frequency, amplitude) allowing efficient removal of tenacious disturbances. An intuitive manmachine interface allows localization, identification, and very precise removal of unwanted audio events. Special functions like automatic detection of clicks, tones, and harmonics significantly accelerate the workflow. A special difference function allows monitoring of the signal portion being removed.
ER  -