Introduction: Aging reduces the ability to understand speech in noise. Hearing rehabilitation is one of the ways to help older people communicate effectively. This study aimed to investigate the effect of vowel auditory training on the improvement of speech-in-noise (SIN) perception among elderly listeners.   Materials and Methods: This study was conducted on 36 elderly ...

In this paper, the signal subspace approach for non-parametric speech enhancement is considered. Several algorithms have been proposed in the literature but only partly analyzed. Here, the different algorithms are compared, and the emphasis is put onto the limiting factors and practical behavior of the estimators. Experimental results show that the signal subspace approach may lead to a signifi...

This paper proposes an exemplar-based speech enhancement method based on high-resolution STFT magnitude spectrograms, where a selection of the nonnegative training data is used as the dictionary to provide a holistic nonnegative representation of the test data. We discuss how this exemplar-based model ensures that the enhanced speech signal falls on the speech manifold, which improves the quali...

Models for automatic speech recognition (ASR) hold detailed information about spectral and spectro-temporal characteristics of clean speech signals. Using these models for speech enhancement is desirable and has been the target of past research efforts. In such model-based speech enhancement systems, a powerful ASR is imperative. To increase the recognition rates especially in low-SNR condition...

We propose a method for the enhancement of intelligibility in scenarios where speech is rendered in a noisy environment. The method is based on the hypothesis that intelligibility is a monotonic function of the degree of preservation of the speech spectral dynamics. The accuracy of the speech spectral dynamics can then be traded against the power of the rendered speech signal. We can either max...

We propose a novel speech enhancement technique based on the hypothesized Wiener filter (HWF) methodology. The proposed HWF algorithm selects a filter for enhancing the input noisy signal by first ‘hypothesizing’ a set of filters and then choosing the most appropriate one for the actual filtering. We show that the proposed HWF can intrinsically offer superior performance to conventional Wiener ...

We propose a signal-adaptive robust time-varying Wiener filter for nonstationary signal estimation/enhancement. This filter uses projections onto local cosine subspaces and a novel “best subspace” algorithm. It allows efficient on-line operation including stable online estimation of design parameters. A statistical analysis is provided, and a speech enhancement example is considered.

It is well known that under noisy conditions we can hear speech much more clearly when we read the speaker's lips. This suggests the utility of audio-visual information for the task of speech enhancement. We propose a method to exploit audio-visual cues to enable speech separation under non-stationary noise and with a single microphone. We revise and extend HMM-based speech enhancement techniqu...

Speech signals are often degraded by additive interference over single channel communication systems. For stationary and well deened noise sources, eeective solutions exist. However, it is often diicult to formulate a model for non-stationary and speech-like noise sources such as cross-talk or multi-speaker babble, which exist in real scenarios. In this paper, we propose a solution to this prob...

A new adaptive speech enhancement system, which utilizes a second-generation wavelet transform (SGWT) decomposition and a novel adaptive subband thresholding technique, is presented. The adaptive thresholding technique is based on accurate estimation of subband segmental signal-to-noise ratio (SegSNR) and voiced/unvoiced classification of the speech. First, the speech signal is segmented and ea...