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» Signal Processing for Robust Speech Recognition
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ICASSP
2011
IEEE
14 years 8 months ago
Deep neural networks for acoustic emotion recognition: Raising the benchmarks
Deep Neural Networks (DNNs) denote multilayer artificial neural networks with more than one hidden layer and millions of free parameters. We propose a Generalized Discriminant An...
André Stuhlsatz, Christine Meyer, Florian E...
TASLP
2008
141views more  TASLP 2008»
15 years 4 months ago
Unsupervised Pattern Discovery in Speech
We present a novel approach to speech processing based on the principle of pattern discovery. Our work represents a departure from traditional models of speech recognition, where t...
A. S. Park, J. R. Glass
129
Voted
ICIP
2000
IEEE
16 years 6 months ago
LIP Contour Extraction Using a Deformable Model
The use of visual information from lip movements can improve the accuracy and robustness of a speech recognition system. Accurate extraction of visual features associated with the...
Alan Wee-Chung Liew, Shu Hung Leung, Wing Hong Lau
CICLING
2003
Springer
15 years 9 months ago
Experiments with Linguistic Categories for Language Model Optimization
In this work1 we obtain robust category-based language models to be integrated into speech recognition systems. Deductive rules are used to select linguistic categories and to matc...
Arantza Casillas, Amparo Varona, Inés Torre...
141
Voted
SPEECH
2011
14 years 11 months ago
SNR loss: A new objective measure for predicting the intelligibility of noise-suppressed speech
Most of the existing intelligibility measures do not account for the distortions present in processed speech, such as those introduced by speech-enhancement algorithms. In the pre...
Jianfen Ma, Philipos C. Loizou