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In exemplar-based speech enhancement systems, lower dimensional features are preferred over the full-scale DFT features for their reduced computational complexity and the ability to better generalize for the unseen cases. But in order to obtain the Wiener-like filter for noisy DFT enhancement, the speech and noise estimates obtained in the feature space(More)
Deep neural network (DNN) based acoustic modelling has been shown to yield significant improvements over Gaussian Mixture Models (GMM) for a variety of automatic speech recognition (ASR) tasks. In addition, it is also becoming popular to use rich speech representations, such as full-resolution spectrograms and perceptually motivated features, as input to(More)
Exemplar-based techniques, where the noisy speech is decomposed as a linear combination of the speech and noise exemplars stored in a dictionary, have been successfully used for speech enhancement in noisy environments. This paper extends this technique to achieve speech dereverberation in noisy environments by means of a nonnegative approximation of the(More)
Deep neural network (DNN) based acoustic modelling has been successfully used for a variety of automatic speech recognition (ASR) tasks, thanks to its ability to learn higher-level information using multiple hidden layers. This paper investigates the recently proposed exemplar-based speech enhancement technique using coupled dictionaries as a pre-processing(More)
Exemplar-based speech enhancement systems work by decomposing the noisy speech as a weighted sum of speech and noise exemplars stored in a dictionary and use the resulting speech and noise estimates to obtain a time-varying filter in the full-resolution frequency domain to enhance the noisy speech. To obtain the decomposition, exemplars sampled in lower(More)
BACKGROUND Ethnomedicine is gaining admiration since years but still there is abundant medicinal flora which is unrevealed through research. The study was conducted to assess the in vitro antimicrobial potential and also determine the minimum inhibitory concentration (MIC) of Citrus sinensis peel extracts with a view of searching a novel extract as a remedy(More)
We present a novel automatic speech recognition (ASR) scheme which uses the recently proposed noise robust exemplar matching framework for speech enhancement in the front-end. The proposed system employs a GMM-HMM back-end to recognize the enhanced speech signals unlike the prior work focusing on template matching only. Speech enhancement is achieved using(More)
Real time speech to text conversion system introduces conversion of the uttered words instantly after the utterance. This paper introduces a unique way of interaction of human and a computer through the specific way ofnatural language processing which is basically a speech recognition system. In this paper nine voice samples were recorded through a(More)
Exemplar-based feature enhancement successfully exploits a wide temporal signal context. We extend this technique with hybrid input spaces that are chosen for a more effective separation of speech from background noise. This work investigates the use of two different hybrid input spaces which are formed by incorporating the full-resolution and modulation(More)