This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
Existing approaches to classifying documents by sentiment include machine learning with features created from n-grams and part of speech. This paper explores a different approach ...
In this paper we investigate the modulation domain as an alternative to the acoustic domain for speech enhancement. More specifically, we wish to determine how competitive the mo...
Abstract— This paper presents and evaluates a hybrid implementation of a low complexity algorithm for speech enhancement, the Adaptive Gain Equalizer (AGE). The AGE is a subband ...
Benny Sallberg, Mattias Dahl, Henrik Akesson, Ingv...
The rapid progress of human genome studies leads to a strong demand of aggregate human DNA data (e.g, allele frequencies, test statistics, etc.), whose public dissemination, howeve...
Xiao-yong Zhou, Bo Peng, Yong Fuga Li, Yangyi Chen...