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...

Contrary to expectations that the coronavirus pandemic would terminate quickly, number of people infected with virus did not decrease worldwide and coronavirus-related deaths continue occur every day. The standard COVID-19 diagnostic test technique used today, PCR testing, requires professional staff equipment, which is expensive takes a long time produce results. In this paper, we propose feat...

Automatic detection of emotions has been evaluated using standard Mel-frequency Cepstral Coefficients, MFCCs, and a variant, MFCC-low, calculated between 20 and 300 Hz, in order to model pitch. Also plain pitch features have been used. These acoustic features have all been modeled by Gaussian mixture models, GMMs, on the frame level. The method has been tested on two different corpora and langu...

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 MFCCs and formant frequencies 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 predict...