In this correspondence, we investigate whether musical noise, which often exists in speech enhanced using spectral subtraction, can be suppressed. Via exploiting some specific characteristics of human speech, we propose a method that can effectively suppress musical noise without noticeable effect on speech intelligibility. Performance assessments confirm that our method is effective.

In this study, we perform a theoretical analysis of the amount of musical noise generated in Bayesian minimum mean-square error speech amplitude estimators. In our previous study, a musical noise assessment based on kurtosis has been successfully applied to spectral subtraction. However, it is difficult to apply this approach to the methods with a decision-directed a priori SNR estimator becaus...

Speech enhancement systems performing in Fourier or wavelet domain usually generate musical noise and distortion. It is possible to reduce musical noise and speech distortion by shaping residual noise. In this paper, we propose to implement a noise shaping method for a wavelet based noise reduction system. For noise shaping, we propose a noise classification method based on spectral shape of in...

An annoying musical residual noise is suffered in most speech enhancement systems. This paper applies a perceptual-based speech enhancement algorithm that considers masking properties to enhance speech signals corrupted by colored noise. Moreover, an optimal smoothing factor which is adapted by the variation of signal to spectral deviation ratio (SSDR) in successive frames is used to reduce the...

The representation of α-stable distributions as scale mixture of normals is exploited to model the noise in musical audio recordings. Markov Chain Monte Carlo inference is used to estimate the clean signal model and the α-stable noise model parameters in a sparse linear regression framework with structured priors. The musical audio recordings were processed both as a whole and in segments by us...

Tempo estimation plays a fundamental role in music analysis, especially for the automatic processing of large amounts of musical data. In this paper, a novel idea to enhance the estimation of the tempo in musical pieces is described, based on an harmonic/noise decomposition. This separation of the signal into a deterministic and a stochastic part is performed by projecting the signal onto its n...

The noise in musical audio recordings is assumed to obey an α-stable distribution. A sparse linear regression framework with structured priors is elaborated. Markov Chain Monte Carlo is used to infer the clean music signal model and the α-stable noise distribution parameters. The musical audio recordings are processed both as a whole and in segments by using a sine-bell window for analysis and ...

OBJECTIVE To investigate the effect of musical training on speech-in-noise (SIN) performance, a complex task requiring the integration of working memory and stream segregation as well as the detection of time-varying perceptual cues. Previous research has indicated that, in combination with lifelong experience with musical stream segregation, musicians have better auditory perceptual skills and...

This paper deals with residual musical noise which results from the perceptual speech enhancement type algorithms and especially using wiener filtering approach. Perceptual speech enhancement techniques perform better than the non perceptual techniques, most of them still return a trouble residual musical noise. This is due to that only noise above the noise masking threshold (NMT) is filtered ...

Instrumental quality assessment serves as an important tool for evaluating and developing noise reduction systems. Commonly three measures are of major interest: the quality of the speech component, the level of noise attenuation, and the amount of musical tones, as a specific type of noise distortion. The first two measures can already be obtained in an instrumental manner in many applications...