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» Bayesian sensing hidden Markov models for speech recognition
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ICMCS
2010
IEEE
164views Multimedia» more  ICMCS 2010»
14 years 11 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...
101
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ICMCS
2005
IEEE
173views Multimedia» more  ICMCS 2005»
15 years 4 months ago
A Multi-Modal Mixed-State Dynamic Bayesian Network for Robust Meeting Event Recognition from Disturbed Data
In this work we present a novel multi-modal mixed-state dynamic Bayesian network (DBN) for robust meeting event classification. The model uses information from lapel microphones,...
Marc Al-Hames, Gerhard Rigoll
ICASSP
2011
IEEE
14 years 2 months ago
Large vocabulary continuous speech recognition with context-dependent DBN-HMMS
The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition. In this work, we pro...
George E. Dahl, Dong Yu, Li Deng, Alex Acero
ICASSP
2011
IEEE
14 years 2 months ago
Automatic recognition of speech without any audio information
This article introduces automatic recognition of speech without any audio information. Movements of the tongue, lips, and jaw are tracked by an Electro-Magnetic Articulography (EM...
Panikos Heracleous, Norihiro Hagita
ICMCS
2006
IEEE
139views Multimedia» more  ICMCS 2006»
15 years 5 months ago
Automatic Semantic Annotation of Images using Spatial Hidden Markov Model
This paper presents a new spatial-HMM(SHMM)for automatically classifying and annotating natural images. Our model is a 2D generalization of the traditional HMM in the sense that b...
Feiyang Yu, Horace Ho-Shing Ip