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ICASSP
2011
IEEE
12 years 11 months ago
Dirichlet Mixture Models of neural net posteriors for HMM-based speech recognition
In this paper, we present a novel technique for modeling the posterior probability estimates obtained from a neural network directly in the HMM framework using the Dirichlet Mixtu...
Balakrishnan Varadarajan, Garimella S. V. S. Sivar...
LREC
2008
146views Education» more  LREC 2008»
13 years 9 months ago
On the Use of Web Resources and Natural Language Processing Techniques to Improve Automatic Speech Recognition Systems
Language models used in current automatic speech recognition systems are trained on general-purpose corpora and are therefore not relevant to transcribe spoken documents dealing w...
Gwénolé Lecorvé, Guillaume Gr...
TSD
2010
Springer
13 years 5 months ago
Hybrid HMM/BLSTM-RNN for Robust Speech Recognition
The question how to integrate information from different sources in speech decoding is still only partially solved (layered architecture versus integrated search). We investigate t...
Yang Sun, Louis ten Bosch, Lou Boves
ICASSP
2009
IEEE
14 years 2 months ago
Independent component analysis for noisy speech recognition
Independent component analysis (ICA) is not only popular for blind source separation but also for unsupervised learning when the observations can be decomposed into some independe...
Hsin-Lung Hsieh, Jen-Tzung Chien, Koichi Shinoda, ...
CSL
2000
Springer
13 years 7 months ago
Detection of phonological features in continuous speech using neural networks
We report work on the first component of a two stage speech recognition architecture based on phonological features rather than phones. The paper reports experiments on three phon...
Simon King, Paul Taylor