Abstract
The paper presents a speech processing method based on spectral subtraction that is effective for reduction of specific rate-dependent noises. Such noises are produced by a variety of different rotation sources such as turbines and car engines. Applicability of convenient spectral subtraction for such noises is limited since their power spectral density (PSD) is connected with rotation rate and therefore constantly changing. The paper shows that in some cases it is possible to compensate variation of PSD by adaptive sampling rate. The signal can be processed in warped time domain that makes noise parameters more stable and easy to estimate. Stabilization of PSD leads to more accurate evaluation of noise parameters and significantly improves result of noise reduction. For de-termination of current rotation rate the proposed method can either use external reference signal or the noisy signal itself applying pitch detector to it. Considering that the noise typically consists of deterministic and stochastic components narrow-band and wide-band components of the noise are removed separately. The method is compared to the recently proposed maximum a posteriori method (MAP).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hadley, M., Milner, B., Harvey, R.: Noise reduction for driver to pit-crew communication in motor racing. In: IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 1, pp. 165–168. IEEE Press, Toulouse (2006)
Milner, B.: Maximum a posteriori estimation of noise from non-acoustic reference signals in very low signal-to-noise ratio environments. In: 12th Annual Conference of the International Speech Communication Association (Interspeech), pp. 357–360. Florence (2011)
Gomez, P., Alvarez, A., Nieto, V., Martinez, R.: Speech enhancement for a car environment using LP residual signal and spectral subtraction. In: 8th European Conference on Speech Communication and Technology (Eurospeech), pp. 1373–1376. Geneva (2003)
Vaseghi, S., Chen, A., McCourt, P.: State based sub-band LP Wiener filters for speech enhancement in car environments. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 213–216. IEEE Press, Istanbul (2000)
Puder, H., Steffens, F.: Improved noise reduction for handsfree car phones utilizing information on vehicle and engine speeds. In: 10th European Signal Processing Conference (EUSIPCO), pp. 1851–1854. Tampere (2000)
Azarov, E., Vashkevich, M., Petrovsky, A.: Instantaneous pitch estimation based on RAPT Framework. In: 20th European Signal Processing Conference (EUSIPCO), pp. 1851–1854. Bucharest (2012)
Petrovsky, A.L., Azarov, E., Petrovsky, A.: Hybrid signal decomposition based on instantaneous harmonic parameters and perceptually motivated wavelet packets for scalable audio coding. Signal Process. 91(6), 1489–1504 (2011)
Azarov, E., Petrovsky, A.: Instantaneous harmonic analysis: audio and speech processing in multimedia systems. Lambert Academic Publishing (2011) (in Russian)
Petrovsky, A., Stankevich, A., Balunowski, J.: The order tracking front-end algorithms in the rotating machine monitoring systems based on the new digital low order filtering. In: International Congresses on Sound and Vibration, pp. 2985–2992. Copenhagen (1999)
Loizou, P.: Speech Enhancement: Theory and Practice. CRC Press, Inc., Boca Raton (2007)
Puder, H.: Single channel noise reduction using time-frequency dependent voice activity detection. In: International Workshop on Acoustic Signal Enhancement, pp. 68–71, USA, Pocono Manor (1999)
Acknowledgments
This work was supported by Belarusian Republican Foundation for Fundamental Research (grant No F14MV-014).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Azarov, E., Vashkevich, M., Petrovsky, A. (2015). Speech Enhancement in Quasi-Periodic Noises Using Improved Spectral Subtraction Based on Adaptive Sampling. In: Ronzhin, A., Potapova, R., Fakotakis, N. (eds) Speech and Computer. SPECOM 2015. Lecture Notes in Computer Science(), vol 9319. Springer, Cham. https://doi.org/10.1007/978-3-319-23132-7_50
Download citation
DOI: https://doi.org/10.1007/978-3-319-23132-7_50
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23131-0
Online ISBN: 978-3-319-23132-7
eBook Packages: Computer ScienceComputer Science (R0)