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ICMCS
2006
IEEE
148views Multimedia» more  ICMCS 2006»
15 years 3 months ago
Acoustically-Driven Talking Face Synthesis using Dynamic Bayesian Networks
Dynamic Bayesian Networks (DBNs) have been widely studied in multi-modal speech recognition applications. Here, we introduce DBNs into an acoustically-driven talking face synthesi...
Jianxia Xue, Jonas Borgstrom, Jintao Jiang, Lynne ...
ICASSP
2011
IEEE
14 years 1 months ago
Maximum likelihood adaptation of histogram equalization with constraint for robust speech recognition
In this paper, we propose a novel feature space adaptation technique to improve the robustness of speech recognition in noisy environments. Histogram equalization (HEQ) is an effe...
Xiong Xiao, Jinyu Li, Engsiong Chng, Haizhou Li
CSL
2002
Springer
14 years 9 months ago
Lightly supervised and unsupervised acoustic model training
The last decade has witnessed substantial progress in speech recognition technology, with todays state-of-the-art systems being able to transcribe unrestricted broadcast news audi...
Lori Lamel, Jean-Luc Gauvain, Gilles Adda
ICASSP
2011
IEEE
14 years 1 months ago
Acoustic model training for non-audible murmur recognition using transformed normal speech data
In this paper we present a novel approach to acoustic model training for non-audible murmur (NAM) recognition using normal speech data transformed into NAM data. NAM is extremely ...
Denis Babani, Tomoki Toda, Hiroshi Saruwatari, Kiy...
ICMCS
2009
IEEE
189views Multimedia» more  ICMCS 2009»
14 years 7 months ago
Emotion recognition from speech VIA boosted Gaussian mixture models
Gaussian mixture models (GMMs) and the minimum error rate classifier (i.e. Bayesian optimal classifier) are popular and effective tools for speech emotion recognition. Typically, ...
Hao Tang, Stephen M. Chu, Mark Hasegawa-Johnson, T...