In this paper we propose a method for enhancement of speech in the presence of additive noise. The objective is to selectively enhance the high signal-to-noise ratio (SNR) regions in the noisy speech in the temporal and spectral domains, without causing signi®cant distortion in the resulting enhanced speech. This is proposed to be done at three di€erent levels. (a) At the gross level, by identi...

In this paper, we investigate the benefits of using an adaptive segmentation of the speech signal in speech enhancement. The adaptive segmentation scheme divides the signal into the longest segments within which stationarity is preserved, thus providing a good time-frequency resolution. The segmentation is performed with the help of an orthogonal library of local cosine bases using a computatio...

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...

In previous work, a speech enhancement algorithm based on phase opponency and a periodicity measure (MPO-APP) was developed for speech recognition. Axiomatic thresholds were used in the MPO-APP regardless of the signal-to-noise ratio (SNR) of the corrupted speech or any characterization of the noise. The current work developed an algorithm for adjusting the threshold in the MPO-APP based on the...

analysis and enhancement which combines signal processing and symbolic processing in a closely coupled manner. The system takes as input both a noisy speech signal and a symbolic description of the speech signal. The system attempts to reconstruct the original speech waveform using symbolic processing to help model the signal and to guide reconstruction. The system uses various signal processin...

The speech enhancement techniques are required to improve the speech signal quality without causing any offshoot in many applications. Recently the growing use of cellular and mobile phones, hands free systems, VoIP phones, voice messaging service, call service centers etc. require efficient real time speech enhancement and detection strategies to make them superior over conventional speech com...

In this paper, a new approach based on the H1 filtering is presented for speech enhancement. This approach differs from the traditional modified Wiener/Kalman filtering approach in the following two aspects: 1) no a priori knowledge of the noise statistics is required; instead the noise signals are only assumed to have finite energy; 2) the estimation criterion for the filter design is to minim...

The improvement of speech intelligibility in hearing aids is a traditional problem that still remains open and unsolved. Modern devices may include signal processing algorithms to improve intelligibility: automatic gain control, automatic environmental classification or speech enhancement. However, the design of such algorithms is strongly restricted by some engineering constraints caused by th...

Traditionally, cerebellar model articulation controller (CMAC) is used in motor control, inverted pendulum robot, and nonlinear channel equalization. In this study, we investigate the capability of CMAC for speech enhancement. We construct a CMAC-based supervised speech enhancement system, which includes offline and online phases. In the offline phase, a paired noisy-clean speech dataset is pre...

The speech signal enhancement is essential to obtain clean speech signal from noisy signal. For multimodal optimization, the natural-inspired algorithms such as Firefly Algorithm (FA) are better. The proposed algorithm contains preprocessing module, optimization module and spectral filtering module. Here, Loizou’s and Aurora databases are considered for signals. In this paper the Perceptional E...