Sciweavers

581 search results - page 24 / 117
» A hierarchical point process model for speech recognition
Sort
View
ICASSP
2011
IEEE
12 years 11 months ago
Learning non-parametric models of pronunciation
As more data becomes available for a given speech recognition task, the natural way to improve recognition accuracy is to train larger models. But, while this strategy yields mode...
Brian Hutchinson, Jasha Droppo
ICASSP
2009
IEEE
14 years 2 months ago
Training and adapting MLP features for Arabic speech recognition
Features derived from Multi-Layer Perceptrons (MLPs) are becoming increasingly popular for speech recognition. This paper describes various schemes for applying these features to ...
J. Park, Frank Diehl, M. J. F. Gales, Marcus Tomal...
ICPR
2000
IEEE
14 years 8 months ago
A Markov Random Field Model for Automatic Speech Recognition
Speech can be represented as a time/frequency distribution of energy using a multi-band filter bank. A Markov random field model, which takes into account the possible time asynch...
Gérard Chollet, Guillaume Gravier, Marc Sig...
CSL
2002
Springer
13 years 7 months ago
Transformation streams and the HMM error model
The most popular model used in automatic speech recognition is the hidden Markov model (HMM). Though good performance has been obtained with such models there are well known limit...
M. J. F. Gales
HCI
2007
13 years 9 months ago
Online Analysis of Hierarchical Events in Meetings
Automatic online analysis of meetings is very important from three points of view: serving as an important archive of a meeting, understanding human interaction processes, and prov...
Xiang Zhang, Guangyou Xu, Xiaoling Xiao, Linmi Tao