Sciweavers

135 search results - page 8 / 27
» Temporal Feature Selection for Noisy Speech Recognition
Sort
View
BMVC
2010
14 years 8 months ago
Local Gaussian Processes for Pose Recognition from Noisy Inputs
Gaussian processes have been widely used as a method for inferring the pose of articulated bodies directly from image data. While able to model complex non-linear functions, they ...
Martin Fergie, Aphrodite Galata
AAAI
2008
15 years 7 days ago
Feature Selection for Activity Recognition in Multi-Robot Domains
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that ar...
Douglas L. Vail, Manuela M. Veloso
ICASSP
2011
IEEE
14 years 1 months ago
Robust speech representation of voiced sounds based on synchrony determination with PLLs
We propose to include synchrony effects, known to exist in the auditory system, to represent voiced parts of the speech signal in a robust way. The system decomposes the input sig...
Patricia A. Pelle, Claudio Estienne, Horacio Franc...
LREC
2010
256views Education» more  LREC 2010»
14 years 11 months ago
WAPUSK20 - A Database for Robust Audiovisual Speech Recognition
Audiovisual speech recognition (AVSR) systems have been proven superior over audio-only speech recognizers in noisy environments by incorporating features of the visual modality. ...
Alexander Vorwerk, Xiaohui Wang, Dorothea Kolossa,...
IEAAIE
2011
Springer
14 years 1 months ago
Multiple Source Phoneme Recognition Aided by Articulatory Features
This paper presents an experiment in speech recognition whereby multiple phoneme recognisers are applied to the same utterance. When these recognisers agree on an hypothesis for th...
Mark Kane, Julie Carson-Berndsen