The enhancement of speech degraded by non-stationary interferers is a highly relevant and difficult task of many signal processing applications. We present a monaural speech enhan...
In this paper, we evaluate the performance of several objective measures in terms of predicting the quality of noisy speech enhanced by noise suppression algorithms. The objective ...
Inspired by recent findings on the similarities between the primary auditory and visual cortex we propose a neural network for speech recognition based on a hierarchical feedforw...
Xavier Domont, Martin Heckmann, Heiko Wersing, Fra...
In this paper we revisit some basic configuration choices of HMMbased speech synthesis, such as waveform sampling rate, auditory frequency warping scale and the logarithmic scali...
This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the fr...