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» Bayesian discriminative adaptation for speech recognition
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ICASSP
2011
IEEE
12 years 8 months ago
Bayesian sensing hidden Markov models for speech recognition
We introduce Bayesian sensing hidden Markov models (BS-HMMs) to represent speech data based on a set of state-dependent basis vectors. By incorporating the prior density of sensin...
George Saon, Jen-Tzung Chien
ICCV
2005
IEEE
13 years 10 months ago
Visual Speech Recognition with Loosely Synchronized Feature Streams
We present an approach to detecting and recognizing spoken isolated phrases based solely on visual input. We adopt an architecture that first employs discriminative detection of ...
Kate Saenko, Karen Livescu, Michael Siracusa, Kevi...
INTERSPEECH
2010
12 years 11 months ago
Improved neural network based language modelling and adaptation
Neural network language models (NNLM) have become an increasingly popular choice for large vocabulary continuous speech recognition (LVCSR) tasks, due to their inherent generalisa...
Junho Park, Xunying Liu, Mark J. F. Gales, Philip ...
ICASSP
2011
IEEE
12 years 8 months ago
Well-calibrated heavy tailed Bayesian speaker verification for microphone speech
The work presented in this paper is an extension of our two previous works [1, 2]. In the first paper [1], we proposed a low dimensional feature (i-vectors) extractor which is su...
Mohammed Senoussaoui, Patrick Kenny, Pierre Dumouc...
ICASSP
2009
IEEE
13 years 11 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...