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ICASSP
2008
IEEE
14 years 3 months ago
HMM adaptation using a phase-sensitive acoustic distortion model for environment-robust speech recognition
In this paper, we present a new approach to HMM adaptation that jointly compensates for additive and convolutive acoustic distortion in environment-robust speech recognition. The ...
Jinyu Li, Li Deng, Dong Yu, Yifan Gong, Alex Acero
TASLP
2010
133views more  TASLP 2010»
13 years 3 months ago
Unsupervised Equalization of Lombard Effect for Speech Recognition in Noisy Adverse Environments
In the presence of environmental noise, speakers tend to adjust their speech production in an effort to preserve intelligible communication. The noise-induced speech adjustments, c...
Hynek Boril, John H. L. Hansen
ICASSP
2011
IEEE
13 years 8 days ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
ICMCS
2005
IEEE
173views Multimedia» more  ICMCS 2005»
14 years 2 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
2009
IEEE
14 years 3 months ago
Unsupervised equalization of Lombard effect for speech recognition in noisy adverse environment
When exposed to environmental noise, speakers adjust their speech production to maintain intelligible communication. This phenomenon, called Lombard effect (LE), is known to consi...
Hynek Boril, John H. L. Hansen