Speech-based gender recognition using linear prediction and mel-frequency cepstral coefficients

The Capacity of Mel Frequency Cepstral Coefficients for Speech Recognition

Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature ex...

Neuro Based Approach for Speech Recognition by Using Mel-frequency Cepstral Coefficients

NEURO BASED APPROACH FOR SPEECH RECOGNITION BY USING MEL-FREQUENCY CEPSTRAL COEFFICIENTS R.L.K. Venkateswarlu1 and R. Vasanthakumari2 1 Department of Information Technology, Sasi Institute of Technology and Engineering, Tadepalligudem, India, E-mail: [email protected]. 2 Perunthalaivar Kamarajar Arts College, Puducherry-605107, India, E-mail: [email protected]. This paper presents continu...

Speech production based on the mel-frequency cepstral coefficients

Speech reconstruction from mel frequency cepstral coefficients and pitch frequency

This paper presents a novel low complexity, frequency domain algorithm for reconstruction of speech from the melfrequency cepstral coe cients (MFCC), commonly used by speech recognition systems, and the pitch frequency values. The reconstruction technique is based on the sinusoidal speech representation. A set of sine-wave frequencies is derived using the pitch frequency and voicing decisions, ...

Analysis and prediction of acoustic speech features from mel-frequency cepstral coefficients in distributed speech recognition architectures.

The aim of this work is to develop methods that enable acoustic speech features to be predicted from mel-frequency cepstral coefficient (MFCC) vectors as may be encountered in distributed speech recognition architectures. The work begins with a detailed analysis of the multiple correlation between acoustic speech features and MFCC vectors. This confirms the existence of correlation, which is fo...