This paper introduces and motivates the use of hybrid robust feature extraction technique for spoken language identification (LID) sys tem. The speech recognizers use a parametric form of a signal to get the most important distinguishable features of speech signal for recognition task. In this paper Mel-frequency cepstral coefficients (MFCC), Perceptual linear prediction coefficients (PLP) alon...

The report proposes a method for detecting the sound events in a basketball game with focusing on detecting cheering sound. MFCC (Mel-frequency cepstral coefficient) features are used to identify the cheering sounds from speeches and other confusing sounds. The mfcc features are fed into a neural network and classified into three classes (cheering, speech, and others). To improve the MFCC-NN pe...

In this paper we have studied two information fusion approaches, namely feature vector concatenation and decision fusion, for the task of reducing error rates in a speaker verification system used in mismatched conditions. Three types of features are fused: Mel Frequency Cepstral Coefficients (MFCC), MFCC with Cepstral Mean Subtraction (CMS) and Maximum Auto-Correlation Values (MACV). We have u...

Parkinson's disease is a recognizable clinical syndrome with variety of causes and presentations; it represents rapidly growing neurodegenerative disorder. Since about 90 percent sufferers have some form early speech impairment, recent studies on tele diagnosis focused the recognition voice impairments from vowel phonations or subjects' discourse. In this paper, we present new approach for dete...

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...