Modified Mel-frequency Cepstrum Coefficient

Detection of Shouted Speech in the Presence of Ambient Noise

This study focuses on the detection of shouted speech in realistic noisy conditions. An automatic system based on modified mel frequency cepstral coefficient (MFCC) feature extraction and Gaussian mixture model (GMM) classification is developed. The performance of the automatic system is compared against human perception measured by a listening test. At moderate noise levels, the automatic syst...

Speech production based on the mel-frequency cepstral coefficients

A Framework for Multilingual Text- Independent speaker identification System

This article evaluates the performance of Extreme Learning Machine (ELM) and Gaussian Mixture Model (GMM) in the context of text independent Multi lingual speaker identification for recorded and synthesized speeches. The type and number of filters in the filter bank, number of samples in each frame of the speech signal and fusion of model scores play a vital role in speaker identification accur...

Mel Frequency Cepstral Coefficients Based Pattern Recognition for Limb Motor Action

This paper proposes a Mel Frequency Cepstral Coefficient (MFCC) based hybrid algorithm for motor imagery classification of Electroencephalogram (EEG) signal for Brain Computer Interface (BCI). The proposed hybrid algorithm contains MFCC with Hjorth Parameter. Regression coefficient method was used for eye artifacts cancellation. The feature extraction method based on the difference of the diffe...

Perceptual Significance of Cepstral Distortion Measures in Digital Speech Processing

Currently, one of the most widely used distance measures in speech and speaker recognition is the Euclidean distance between mel frequency cepstral coefficients (MFCC). MFCCs are based on filter bank algorithm whose filters are equally spaced on a perceptually motivated mel frequency scale. The value of mel cepstral vector, as well as the properties of the corresponding cepstral distance, are d...