Speech and Spectral Landscapes using Mel-Frequency Cepstral Coefficients Signal Processing

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, ...

Speech production based on the 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...

Mel Frequency Cepstral Coefficients for Music Modeling

We examine in some detail Mel Frequency Cepstral Coefficients (MFCCs) the dominant features used for speech recognition and investigate their applicability to modeling music. In particular, we examine two of the main assumptions of the process of forming MFCCs: the use of the Mel frequency scale to model the spectra; and the use of the Discrete Cosine Transform (DCT) to decorrelate the Mel-spec...

Improving the noise-robustness of mel-frequency cepstral coefficients for speech processing

In this paper we study the noise-robustness of mel-frequency cepstral coefficients (MFCCs) and explore ways to improve their performance in noisy conditions. Improvements based on a more accurate model of the early auditory system are suggested to make the MFCC features more robust to noise while preserving their class discrimination ability. Speech versus non-speech classification and speech r...