Change search
ReferencesLink to record
Permanent link

Direct link
Spectral Subtraction Using Model-based Spectra
Responsible organisation
1999 (English)Conference paper (Refereed) Published
Abstract [en]

When using a mobile phone with a handsfree equipment in a vehicle it is difficult to have a relaxed conversation due to the high noise level. The noisy environment gives raise to a poor signal to noise ratio since the handsfree microphone picks up the background noise as well as the speech. By using speech enhancement processing, the quality of the conversation will be enhanced. This paper introduces a speech enhancement algorithm based on the spectral subtraction method. The method uses estimates of the noise spectrum and the noisy speech spectrum to form an SNR-based gain function, which is used for filtering the microphone signal. There are two different classes of spectrum estimation techniques non-parametric and parametric. Parametric estimation methods are based on a model of the underlying signal in order to estimate the spectrum.Furthermore a tool for assessing the accuracy of the estimations in situations when few data is available is applied, known as the bootstrapmethod. The spectral subtraction method, combined with different spectrum estimation techniques, are evaluated using real-world signals recorded in a car.

Place, publisher, year, edition, pages
Lyngby, Denmark, 1999.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-9703Local ID: oai:bth.se:forskinfoA446A4572FC2ADF5C1256C6A004536FFOAI: oai:DiVA.org:bth-9703DiVA: diva2:837623
Conference
the Sixth International Congress on Sound and Vibration
Available from: 2012-09-18 Created: 2002-11-07 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

fulltext(201 kB)8 downloads
File information
File name FULLTEXT01.pdfFile size 201 kBChecksum SHA-512
52dd7e4f8f07d71ba6b03d2380bf88949b684d0bc9cb683bbc0bce23bf89e92f874dd57fb63825ed8fd219449efd89b017901b59762000d0ec079bcad9fbd986
Type fulltextMimetype application/pdf
fulltext(224 kB)9 downloads
File information
File name FULLTEXT02.pdfFile size 224 kBChecksum SHA-512
2a0c47f6d6a218b228e3d15527bc99eabc00af94634eee6fd8b86e9aef289551d3fd65cb34d18a4d873c56156331e0a43d1bb2f9f93a463a9ab7895d3699ade7
Type fulltextMimetype application/pdf

Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 17 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 20 hits
ReferencesLink to record
Permanent link

Direct link