For Mel Nimmer

Mel-Wiener Filter for Mel-LPC Based Speech Recognition

Mel-cepstrum-based steganalysis for VoIP steganography

Steganography and steganalysis in VoIP applications are important research topics as speech data is an appropriate cover to hide messages or comprehensive documents. In our paper we introduce a Mel-cepstrum based analysis known from speaker and speech recognition to perform a detection of embedded hidden messages. In particular we combine known and established audio steganalysis features with t...

An improved mel-wiener filter for mel-LPC based speech recognition

We previously proposed a Mel-Wiener filter to enhance Mel-LPC spectra in presence of additive noise. The proposed filter was estimated based on minimization of sum of square error on the linear frequency scale and efficiently implemented in the autocorrelation domain without denoising input speech. In the previously proposed system we segregated speech and noise using an energy based VAD and a ...

Comments of Mel J

I am writing this letter on behalf of the International Diatomite Producers Association (“IDPA”), a trade association of producers of diatomaceous earth products that was formed in 1987. IDPA includes in its membership companies both doing business and operating facilities in the state of California. IDPA sponsored one of the principal epidemiology studies relating to crystalline silica exposur...

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...