In this paper, we propose novel techniques for feature parameter extraction based on MFCC and feature recognition using dynamic time warping algorithm for application in speaker-independent isolated digits recognition. Using the proposed Weighted MFCC (WMFCC), we achieve low computational overhead for the feature recognition stage since we use only 13 weighted MFCC coefficients instead of the c...

The mel frequency cepstral coefficient (MFCC) is one of the most important features required among various kinds of speech applications. In this paper, the first chip for speech features extraction based on MFCC algorithm is proposed. The chip is implemented as an intellectual property, which is suitable to be adopted in a speech recognition system on a chip. The computational complexity and me...

This paper presents a new feature for speaker identification called perceptual log area ratio (PLAR). PLAR is closely related to the log area ratio (LAR) feature. PLAR is derived from the perceptual linear prediction (PLP) rather than the linear predictive coding (LPC). The PLAR feature derived from PLP is more robust to noise than the LAR feature. In this paper, PLAR, LAR and MFCC features wer...

This work proposes a novel method of predicting formant frequencies from a stream of mel-frequency cepstral coefficients (MFCC) feature vectors. Prediction is based on modelling the joint density of MFCC vectors and formant vectors using a Gaussian mixture model (GMM). Using this GMM and an input MFCC vector, two maximum a posteriori (MAP) prediction methods are developed. The first method pred...

In our previous work [1, 2], we have introduced Fepstrum an improved modulation spectrum estimation technique that overcomes certain theoretical as well as practical shortcomings in the previously published modulation spectrum related techniques[7, 8, 9]. In this paper, we provide further extensive ASR results using the Tandem processed Fepstrum features over the TIMIT corpus. The results are c...

This paper describes the principle of MFCC feature extraction and the knowledge of human auditory masking effect in order to introduce a modified-MFCC feature extraction that can improve the robustness of speech recognition systems.

Speaker recognition is an ability to identify speaker’s characteristics based from spoken language. The purpose of this study gender speakers on audio recordings. objective evaluate the accuracy rate technique differentiate and also determine performance classify even when using self-acquired Audio forensics uses voice recordings as part evidence solve cases. This mainly conducted provide easie...