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» A Markov Random Field Model for Automatic Speech Recognition
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ICPR
2002
IEEE
14 years 9 months ago
Relational Graph Labelling Using Learning Techniques and Markov Random Fields
This paper introduces an approach for handling complex labelling problems driven by local constraints. The purpose is illustrated by two applications: detection of the road networ...
Denis Rivière, Jean-Francois Mangin, Jean-M...
ICASSP
2011
IEEE
12 years 11 months ago
MLP based phoneme detectors for Automatic Speech Recognition
Phoneme posterior probabilities estimated using Multi-Layer Perceptrons (MLPs) are extensively used both as acoustic scores and features for speech recognition. In this paper we e...
Samuel Thomas, Patrick Nguyen, Geoffrey Zweig, Hyn...
SAC
2003
ACM
14 years 1 months ago
A Markov Random Field Model of Microarray Gridding
DNA microarray hybridisation is a popular high throughput technique in academic as well as industrial functional genomics research. In this paper we present a new approach to auto...
Mathias Katzer, Franz Kummert, Gerhard Sagerer
ICASSP
2009
IEEE
14 years 2 months ago
Experimenting with a global decision tree for state clustering in automatic speech recognition systems
In modern automatic speech recognition systems, it is standard practice to cluster several logical hidden Markov model states into one physical, clustered state. Typically, the cl...
Jasha Droppo, Alex Acero
ICMCS
2010
IEEE
164views Multimedia» more  ICMCS 2010»
13 years 8 months ago
Exploiting multimodal data fusion in robust speech recognition
This article introduces automatic speech recognition based on Electro-Magnetic Articulography (EMA). Movements of the tongue, lips, and jaw are tracked by an EMA device, which are...
Panikos Heracleous, Pierre Badin, Gérard Ba...