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ICASSP
2011
IEEE
12 years 10 months ago
Iterative feature normalization for emotional speech detection
Contending with signal variability due to source and channel effects is a critical problem in automatic emotion recognition. Any approach in mitigating these effects however has t...
Carlos Busso, Angeliki Metallinou, Shrikanth S. Na...
ICMI
2004
Springer
263views Biometrics» more  ICMI 2004»
13 years 11 months ago
Analysis of emotion recognition using facial expressions, speech and multimodal information
The interaction between human beings and computers will be more natural if computers are able to perceive and respond to human non-verbal communication such as emotions. Although ...
Carlos Busso, Zhigang Deng, Serdar Yildirim, Murta...
ICASSP
2011
IEEE
12 years 10 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...
ICMCS
2006
IEEE
140views Multimedia» more  ICMCS 2006»
14 years 8 days ago
Evolutionary Feature Generation in Speech Emotion Recognition
Feature sets are broadly discussed within speech emotion recognition by acoustic analysis. While popular filter and wrapper based search help to retrieve relevant ones, we feel th...
Björn Schuller, Stephan Reiter, Gerhard Rigol...
ICASSP
2010
IEEE
13 years 6 months ago
Analysis of phone posterior feature space exploiting class-specific sparsity and MLP-based similarity measure
Class posterior distributions have recently been used quite successfully in Automatic Speech Recognition (ASR), either for frame or phone level classification or as acoustic featu...
Afsaneh Asaei, Benjamin Picart, Hervé Bourl...