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.
https://www.aes.org/e-lib/browse.cfm?elib=14899
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.
Learn more about the AES E-Library
Start a discussion about this paper!
