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Psychoacoustical and neurophysiological results indicate that spectro-temporal modulations play an important role in sound perception. Speech signals, in particular, exhibit distinct spectro-temporal patterns which are well matched by receptive fields of cortical neurons. In order to improve the performance of automatic speech recognition (ASR) systems a(More)
Dieses Technische Dokument gehört zu Teilprojekt 1: Modalitätsspezifische Analysatoren Das diesem Technischen Dokument zugrundeliegende Forschungsvorhaben wurde mit Mitteln des Bundesministeriums für Bildung und Forschung unter dem Förderkennzeichen 01 IL 905 gefördert. Die Verantwortung für den Inhalt liegt beim Autor. ABSTRACT A novel type of feature(More)
Recent results from physiological and psychoacoustic studies indicate that spectrally and temporally localized time-frequency envelope patterns form a relevant basis of auditory perception. This motivates new approaches to feature extraction for automatic speech recognition (ASR) which utilize two-dimensional spectro-temporal modulation filters. The paper(More)
Cyanidium caldarium was cultured at 20 and 55 C and harvested during exponential growth phase. Comparative lipid studies on each cell type show a decrease by one-half of the total lipid in cells grown at 55 C over cells grown at 20 C. While the distribution of lipid into each of five lipid classes was not influenced by high temperature (55 C), the degree of(More)
A main task for computational auditory scene analysis (CASA) is to separate several concurrent speech sources. From psychoa-coustics it is known that common onsets, common amplitude modulation and sound source direction are among the important cues which allow the separation for the human auditory system. A new algorithm is presented here, that performs(More)
In this paper a new approach is presented for estimating the long-term speech-to-noise ratio (SNR) in individual frequency bands that is based on methods known from automatic speech recognition (ASR). It uses a model of auditory perception as front end, physiologically and psychoacoustically motivated sigma-pi cells as secondary features, and a linear or(More)
A novel noise suppression scheme for speech signals is proposed which is based on a neurophysiologically-motivated estimation of the local signal-to-noise ratio (SNR) in different frequency channels. For SNR-estimation, the input signal is transformed into so-called Amplitude Modulation Spectrograms (AMS), which represent both spectral and temporal(More)