@INPROCEEDINGS{0770Kim2004, AUTHOR = {Hyoung-Gook Kim and Thomas Sikora}, TITLE = {Speech Enhancement based on Smoothing of Spectral Noise Floor}, BOOKTITLE = {INTERSPEECH 2004 - ICSLP}, YEAR = {2004}, MONTH = oct, ADDRESS = {Jeju Island, Korea}, PDF = {http://elvera.nue.tu-berlin.de/files/0770Kim2004.ps}, ABSTRACT = {This paper presents robust speech enhancement using noise estimation based on smoothing of spectral noise floor (SNF) for nonstationary noise environments. The spectral gain function is obtained by well-known log-spectral amplitude (LSA) estimation criterion associated with the speech presence uncertainty. The noise estimate is given by averaging actual spectral power values, using a smoothing parameter that depends on smoothing of spectral noise floor. The noise estimator is very simple but achieves a good tracking capability for a nonstationary noise. Its enhanced speech is free of musical tones and reverberation artifacts and sounds very natural compared to methods using other short-time spectrum attenuation techniques. The performance is measured by the segmental signal-to-noise ratio (SNR), the speech/speaker recognition accuracy and the speaker change detection rate for the audio segmentation using MFCC-features (Melscale Frequency Cepstral Coefficients) in comparison to other single microphone noise reduction methods.} }