This paper describes a new algorithm to enhance and recognise noisy speech when only the noisy signal is available. The system uses autoregressive hidden Markov models (HMMs) to model the clean speech and noise and combines these to form a model for the noisy speech. The probability framework developed is then used to reestimate the noise models from the corrupted speech waveform and the proces...

The aim of the Speech Enhancement system is to improve the quality of noisy speech signal. This paper emphasize on enhancement of noisy speech by using Affine Projection Algorithm (APA) and Kernel Affine Projection Algorithm (KAPA). Noise is present everywhere in the environment, So Kernel adaptive filters are used to enhance noisy speech signal and shows the good improvement in increasing the ...

Example-based speech enhancement is a promising singlechannel approach for coping with highly nonstationary noise. Given a noisy speech input, it first searches in a noisy speech corpus for the noisy speech examples that best match the input. Then, it concatenates the clean speech examples that are paired with the matched noisy examples to obtain an estimate of the underlying clean speech compo...

Multiple-model based speech recognition (MMSR) has been shown to be quite successful in noisy speech recognition. Since it employs multiple hidden Markov model (HMM) sets that correspond to various noise types and signal-to-noise ratio (SNR) values, the selected acoustic model can be closely matched with the test noisy speech, which leads to improved performance when compared with other state-o...

A practical speech enhancement system consists of two major components, the estimation of noise power spectrum, and the estimation of speech.In single channel speech enhancement systems, most algorithms require an estimation of average noise spectrum since a secondary channel is not available. This requires a reliable speech/silence detector. Thus the speech/silence detection can be a determini...

Most noisy speech enhancement methods result in partial suppression and distortion of speech spectrum. At instances when the local signal-to-noise ratio at a frequency band is very low speech partials are often obliterated. In this paper a method for enhancement and restoration of noisy speech based on a harmonic-noise model (HNM) is introduced. A HNM imposes a temporal-spectral structure that ...

A novel technique is presented to design the signal subspace speech enhancement based on perceptual post filtering. Firstly, by subspace filter the noisy speech is enhanced. The underlying principle is to decompose the vector space of the noisy signal into a signal plus noise subspace and a noise subspace. The decomposition can theoretically be performed by applying the Karhunen-Loeve transform...

Most noisy speech enhancement methods result in partial suppression and distortion of speech spectrum. At instances when the local signal-to-noise ratio at a frequency band is very low speech partials are often obliterated. In this paper a method for enhancement and restoration of noisy speech based on a harmonic-noise model (HNM) is introduced. A HNM imposes a temporal-spectral structure that ...