Speech Processing Dec. 11, 2006 YOUNG-CHAN LEE Spectrum Enhancement Speech Processing Dec. 11, 2006 YOUNG-CHAN LEE
Spectrum enhancement Goal : find noiseless spectrum for speech signal Regard corrupted signal consist of noise, pure signal and background noise. Same spectrum components
Equation-method(1) Spectrum enhancement Global information (average) Local information (average) Estimate of background
Spectrogram
New Equation – method-(2) Analysis of each component and find parameters Part – 1 (Global energy) Part – 2 (local energy) Part – 3 (Background estimate) Part – 4 (Floor)
Additive Noise Suppression Suppress noise compare to speech signal
Part - 1 Spectrum and global energy
Part - 2 Spectrum and local energy
Part - 3 Spectrum and background estimate
Estimate of Background Before background estimate New background estimate
Part - 4 Spectrum and floor
Overall spectrum
Comparison of enhanced spectrum
File list (used same parameters) Examples File list (used same parameters) CCW170007_000.ulaw CCW170007_001.ulaw CCW170007_002.ulaw CCW170007_003.ulaw CCW170007_004.ulaw CCW170007_005.ulaw CCW170007_006.ulaw CCW170007_007.ulaw CCW170007_008.ulaw CCW170007_009.ulaw
Example1 (CCW1700007_000.ulaw)
Continue (spectrum)
Example2 (CCW1700007_001.ulaw)
Continue (spectrum)
Example3 (CCW1700007_002.ulaw)
Continue (spectrum)
Example4 (CCW1700007_003.ulaw)
Continue (spectrum)
Example5 (CCW1700007_004.ulaw)
Continue (spectrum)
Example6 (CCW1700007_005.ulaw)
Continue (spectrum)
Example7 (CCW1700007_006.ulaw)
Continue (spectrum)
Example8 (CCW1700007_007.ulaw)
Continue (spectrum)
Example9 (CCW1700007_008.ulaw)
Continue (spectrum)
Example10 (CCW1700007_009.ulaw)
Continue (spectrum)
Conclusions Global energy, local energy, background estimate greatly affected to build enhanced spectrum. Part3 and part4 showed good spectrum estimation. In new method, we don’t need to change parameter values according to input files.
MATLAB Demo
Thank you! Merry Christmas