Linear prediction analysis is a crucial technique used in speech coding to compress speech
signals and facilitate their reliable transmission over limited bandwidth or storage space …

This paper addresses the problem of feature compensation in the log-spectral domain by
using the missing-data (MD) approach to noise robust speech recognition, that is, the log …

This paper presents a feature compensation framework based on minimum mean square
error (MMSE) estimation and stereo training data for robust speech recognition. In our …

In this paper we present a new mitigation technique for lost speech frames transmitted over
loss-prone packet networks. It is based on an MMSE estimation from the last received frame …

This paper proposes a novel approach for noise-robust speech recognition which combines
a missing-data (MD) derived spectral reconstruction technique and uncertainty decoding …

A novel approach, based on robust regression with normalized score fusion (namely
Normalized Scores following Robust Regression Fusion: NSRRF), is proposed for …

Many studies have proposed solutions to overcome the degradation of network speech
recognition (NSR) caused by packet loss and jitter. The most popular cloud-based speech …

De entre los problemas que aún se encuentran abiertos en el campo del reconocimiento
automático del habla, uno de los que suscitan mayor interés entre la comunidad científica …

In this Ph. D. dissertation the influence of packet losses on speech recognition is analyzed
and different solutions to prevent, reduce and conceal their effects are developed. The …

In the last two decades, there has been an important increase in research on speech
technology in Spain, mainly due to a higher level of funding from European, Spanish and …