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Motivated by the human ability to maintain a high level of speech recognition when large parts of the spectrogram are masked (i.e. dominated) by noise, the original "missing data" (MD) approach to noise robust speech recognition was based on the paradigm w ...
As sampling is taking place, the most active regions of the spectrum can be identified (i.e. the vicinity of spectral peaks). By selectively increasing the spectral density within those regions improves the quality of the total spectral representation redu ...
A heterodyne laser Doppler interferometer operating up to 100 MHz with an optical vibration excitation function was implemented to enable frequency detection of nanocantilevers. By using the stimulant of a network analyzer to sweep the modulation frequency ...
In each season when the DA pulsating white dwarf G29–38 has been observed, its period spectrum appears very different, but it always contains a forest of harmonics and cross-frequencies. The ratio of the amplitude of these non-linear frequencies Ac to the ...
In this paper, we present an efficient measurement technique for the analysis of power line communication (PLC) signals. The frequency spectrum associated with PLC signals extends from 1 MHz to 30 MHz. The proposed technique can be applied to a network con ...
The development of high power CW gyrotrons for ECRH heating of fusion relevant plasmas has been in progress for several years in a joint collaboration between different European research institutes and an industrial partner. Two development are on going, a ...
This paper proposes a simple, computationally efficient 2-mixture model approach to discriminate between speech and background noise at the magnitude spectrogram level. It is directly derived from observations on real data, and can be used in a fully unsup ...
Recently, entropy measures at different stages of recognition have been used in automatic speech recognition (ASR) task. In a recent paper, we proposed that formant positions of a spectrum can be captured by multi-resolution spectral entropy feature. In th ...
Recently, entropy measures at different stages of recognition have been used in automatic speech recognition (ASR) task. In a recent paper, we proposed that formant positions of a spectrum can be captured by multi-resolution spectral entropy feature. In th ...
We present a new framework for processing point-sampled objects using spectral methods. By establishing a concept of local frequencies on geometry, we introduce a versatile spectral representation that provides a rich repository of signal processing algori ...