Fast Fourier Transform (FFT) plays an important role in the field of digital signal processing. High performance FFT processors are widely used in different application, such as speech processing, image processing, and communication system. In this paper, we proposed a novel register array based low power FFT processor for Mel Frequency Cepstral Coefficient (MFCC). Compared with [9-12], this no...

the mel frequency cepstral coefficients are the most widely used feature in speech recognition but they are very sensitive to noise. in this paper to achieve a satisfactorily performance in automatic speech recognition (asr) applications we introduce a noise robust new set of mfcc vector estimated through following steps. first, spectral mean normalization is a pre-processing which applies to t...

Molecular fractionation with conjugate caps (MFCC) method is introduced for the efficient estimation of quantum mechanical (QM) interaction energies between nanomaterial (carbon nanotube, fullerene, and graphene surface) and ligand (charged and neutral). In the calculations, nanomaterials are partitioned into small fragments and conjugated caps that are properly capped, and the interaction ener...

In this paper, the use of sonority measure as an acoustic feature of the speech signal for continuous automatic speech recognition is described. The representation of sonority extent of sounds is made with a help of spectrum derivation. Therefore, a novel articulatory motivated acoustic feature expressing the sonority is named spectrum derivative feature. The new feature is tested in combinatio...

Recognition rate of noisy short utterance is lower, the two main factors are the inadequate training data and utterance polluted by noisy seriously. In this paper, we proposed corresponding algorithms. First, noise and speech are regarded as parallel information, we use FastICA algorithm to separate pure speech and noise. And then, we use differences detecting and eliminating algorithm (DDAEA) ...

Phone Log-Likelihood Ratios (PLLR) have been recently proposed as alternative features to MFCC-SDC for iVector Spoken Language Recognition (SLR). In this paper, PLLR features are first described, and then further evidence of their usefulness for SLR tasks is provided, with a new set of experiments on the Albayzin 2010 LRE dataset, which features wide-band multi speaker TV broadcast speech on si...

In this paper we propose a new coding algorithm based on nonlinear prediction: the Neural Predictive Coding model which is an extension of the classical LPC one. The features performances are estimated by two different methods: the ArithmeticHarmonic Sphericity (AHS) and the Auto-Regressive Vectorial Models (ARVM). Two different methods are proposed for the coding method based on the Neural Pre...