We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series
analysis, with applications to learning models of human pose and motion from high …

This book presents an interactive multimodal approach for efficient transcription of
handwritten text images. This approach, rather than full automation, assists the expert in the …

Spectral restoration methods for speech enhancement aim to remove noise components in
noisy speech signals by using a gain function in the spectral domain. How to design the gain …

This paper proposes a sequential coupling of a hidden Markov model (HMM) recognizer for
offline handwritten English sentences with a probabilistic bottom-up chart parser using …

A re-scoring strategy is proposed that makes it feasible to capture more long-distance
dependencies in the natural language. Two pass strategies have become popular in a …

We consider the Gaussian framework for reverberant audio source separation, where the
sources are modeled in the time-frequency domain by their short-term power spectra and …

In this paper, we describe the recent trend in automatic speech recognition. First, we should
point out that the current art of speech recognition by machines is admittedly inferior to the …

The amount of digitized legacy documents has been rising dramatically over the last years
due mainly to the increasing number of on-line digital libraries publishing this kind of …

Although handwritten text recognition has been studied for some years, only few authors
have used statistical language models to increase the performance of their recognizers. In …

In this paper, we investigate the relative noise robustness of dynamic and static spectral
features in speech recognition. It is found that the dynamic cepstrum is more robust to …