Many short-time Fourier transform (STFT) based singlechannel speech enhancement algorithms are focused on estimating clean speech spectral amplitude from the noisy observed signal in order to suppress the additive noise. To this end, the state-of-the-art speech enhancement algorithms, employ noisy amplitude information and correspondingly a priori and a posteriori SNRs while they use no informa...

This paper proposes learning-based methods for mapping a sparse representation of noisy speech to state likelihoods in an automatic speech recognition system. We represent speech as a sparse linear combination of exemplars extracted from training data. The weights of exemplars are mapped to speech state likelihoods using Ordinary Least Squares (OLS) and Partial Least Squares (PLS) regression. R...

Every speech recognition system contains a speech/non-speech detection stage. Detected speech sequences are only passed through the speech recognition stage later on. In a very noisy environment, the noise detection stage is generally responsible for most of the recognition errors. Indeed, many detected noisy periods can be recognized as a vocabulary word. This manuscript provides solutions to ...

Using visual information in speech recognition has been an area of interest because it can signi cantly improve the speech recognition e ciency in the conditions where audio only recognition su ers due to noisy environment. In this paper, we present a new approach to combine audio and video to improve the robustness of the speech recognition system in the noisy environments. We also compare the...

The aim of this paper is to use visual speech information to create Wiener filters for audio speech enhancement. Wiener filters require estimates of both clean speech statistics and noisy speech statistics. Noisy speech statistics are obtained from the noisy input audio while obtaining clean speech statistics is more difficult and is a major problem in the creation of Wiener filters for speech ...

BACKGROUND AND OBJECTIVES For the hearing-impaired population, quality of sound when listening to speech on mobile phone is often dissatisfactory. Even with a turning up the volume, they feel mobile speech unclear and desire the mobile sounds to be amplified as suited for the hearing characteristics. The purpose of this study was to estimate the appropriateness of NAL-NL1 fitting formula for th...

The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds....

In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...

In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...

In mobile devices, perceived speech signal degrades significantly in the presence of background noise as it reaches directly at the listener's ears. There is a need to improve the intelligibility and quality of the received speech signal in noisy environments by incorporating speech enhancement algorithms. This paper focuses on speech enhancement method including auditory masking propertie...