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» Introduction to speech recognition using neural networks
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INTERSPEECH
2010
13 years 3 months ago
Using a DBN to integrate sparse classification and GMM-based ASR
The performance of an HMM-based speech recognizer using MFCCs as input is known to degrade dramatically in noisy conditions. Recently, an exemplar-based noise robust ASR approach,...
Yang Sun, Jort F. Gemmeke, Bert Cranen, Louis ten ...
IJISTA
2007
124views more  IJISTA 2007»
13 years 8 months ago
Incremental learning for spoken affect classification and its application in call-centres
: This paper introduces a system for real-time incremental learning in a call-centre environment. The classifier used is a Support Vector Machine (SVM) and it is applied to telepho...
Donn Morrison, Ruili Wang, W. L. Xu, Liyanage C. D...
ESANN
2003
13 years 10 months ago
Meter value recognition using locally connected hierarchical networks
This paper describes a two-stage system for the recognition ge meter values. A feed-forward Neural Abstraction Pyramid is initialized in an unsupervised manner and trained in a sup...
Sven Behnke
EVOW
2009
Springer
14 years 21 days ago
Efficient Signal Processing and Anomaly Detection in Wireless Sensor Networks
In this paper the node-level decision unit of a self-learning anomaly detection mechanism for office monitoring with wireless sensor nodes is presented. The node-level decision uni...
Markus Wälchli, Torsten Braun
ICASSP
2011
IEEE
13 years 16 days ago
Large vocabulary continuous speech recognition with context-dependent DBN-HMMS
The context-independent deep belief network (DBN) hidden Markov model (HMM) hybrid architecture has recently achieved promising results for phone recognition. In this work, we pro...
George E. Dahl, Dong Yu, Li Deng, Alex Acero