One of the main problems in sound restoration of valuable historical recordings includes the noise reduction. We have been proposing and continuing to improve the noise reduction method utilized by inharmonic analysis such as GHA (Generalized Harmonic Analysis). Algorithm of GHA frequency extraction enables to extract arbitrary frequency components. In this report, we aimed at more accurate frequency identification from noisy signals to divide analyzed frequency section into multi-bands before analysis: this algorithm is named as Multi-band GHA (MGHA). The simulation of frequency analysis in noise-free condition indicated that MGHA is more effective than GHA for the extraction of low frequency components in the condition of both lower window length and amount of frequency components. However, excluding the case of both lower window length and amount of frequency components, GHA identifies frequency components more precisely. Furthermore the result of frequency analysis in condition with steady noise shows that MGHA can be more effectively applied to the case of short window length, many frequency components and low S/N.
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can
subscribe to this RSS feed.
Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.
