In this paper we present a two stage noise reduction algorithm for speech enhancement. The speech noise removal algorithm is based on a two stage noise filtering LSAHT by log spectral amplitude speech estimator (LSA) and harmonic tunneling (HT) with spectral subtraction. The performance of the system is measured by the segmental signal-to-noise ratio, mean opinion score (MOS) tests, and the rec...

Degrading the quality and intelligibility of the speech signals, background noise is a severe problem in communication and other speech related systems. In order to get rid of this problem, it is important to enhance the original speech signal mainly through noise reduction. Speech enhancement is the term used to describe such algorithms and devices whose purpose is to improve some perceptual a...

Speech de-noising algorithms often suffer from introduction of artifacts, either by removal of parts of the speech signal, or imperfect noise reduction causing the remaining noise to sound unnatural and disturbing. This contribution proposes to spatially distribute monaural noisy speech signals based on single-channel source separation, in order to improve the perceived speech quality. Stereo u...

In this paper, we present a new single-channel noise reduction method that integrates compensation and soft masking into the same statistical model assumptions for noise-robust speech recognition. By utilizing a Gaussian mixture model(GMM) as a pre-knowledge of speech and added noise signals, the proposed method can effectively restore clean speech spectra and separate out ambient noises from a...

This paper presents a speech enhancement using a noise estimation based on the ratio of the noisy speech and its minimum (NSMR) for non-stationary noise environments. The noise estimator is a very simple but highly effective real time approach for single channel noise reduction. The enhanced speech is free of musical tones and reverberation artifacts and sounds very natural compared to methods ...