Signal Processing Ideas

Description:
Pitch Estimation module (ACF+CEP) + Spectral estimation module (STChT) + Noise spectrum estimation (adaptive Quantile) + Noise removal (anything from Wiener filter to the most complicated TF-based methods)

Building blocks:

• Pitch estimation. An enhanced version of the reindexing method published in [1] was used as a basis for this module.

• Short-Time Fan Chirp (STFCh)Transform. We use the fast version of the Fan-Chirp transform [2].

• Noise estimation: this module is based on the well known quantile filtration idea [3], acc. to which the noisy background can be estimated by applying empirically defined percentage of the sorted time-frequency atoms.

• Noise suppression: The “speech enhancement” is happening in this module. It applyes the estimated noise spectrum, and removes it from the representation provided by the STHChT module.

References:
[1] Képesi, M and Weruaga, L.: “Harmonic Tracking based Short-Time Chirp Analysis of Speech Signals”, Robust2004 COST278 & ISCA ITRW Workshop on Robustness Issues in Conversational Interaction, 30th and 31st August 2004, University of East Anglia, Norwich, UK
[2] L. Weruaga, M. Kepesi, “The fan-chirp transform for non-stationary harmonic sounds”, Signal Proc., vol. 87, pp. 1504-1522, 2007.

Related Work:
[3] Stahl, V.; Fischer, A.; Bippus, R: “Quantile based noise estimation for spectral subtraction and Wiener filtering”, Acoustics, Speech, and Signal Processing, 2000. Volume 3, Issue , 2000 Page(s):1875 – 1878 vol.3
[4] Sidsel Marie Norholm, PhD Thesis, 2015