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» Subspace Gaussian Mixture Models for speech recognition
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ICASSP
2011
IEEE
14 years 1 months ago
Arccosine kernels: Acoustic modeling with infinite neural networks
Neural networks are a useful alternative to Gaussian mixture models for acoustic modeling; however, training multilayer networks involves a difficult, nonconvex optimization that...
Chih-Chieh Cheng, Brian Kingsbury
ICASSP
2010
IEEE
14 years 9 months ago
Towards multi-speaker unsupervised speech pattern discovery
In this paper, we explore the use of a Gaussian posteriorgram based representation for unsupervised discovery of speech patterns. Compared with our previous work, the new approach...
Yaodong Zhang, James R. Glass
ICPR
2010
IEEE
14 years 7 months ago
Use of Line Spectral Frequencies for Emotion Recognition from Speech
We propose the use of the line spectral frequency (LSF) features for emotion recognition from speech, which have not been been previously employed for emotion recognition to the b...
Elif Bozkurt, Engin Erzin, Çigdem Eroglu Er...
TASLP
2010
101views more  TASLP 2010»
14 years 4 months ago
Gaussian Model-Based Multichannel Speech Presence Probability
The knowledge of the target speech presence probability in a mixture of signals captured by a speech communication system is of paramount importance in several applications includi...
Mehrez Souden, Jingdong Chen, Jacob Benesty, Sofi&...
NAACL
1994
14 years 11 months ago
Microphone-Independent Robust Signal Processing Using Probabilistic Optimum Filtering
A new mapping algorithm for speech recognition relates the features of simultaneous recordings of clean and noisy speech. The model is a piecewise nonfinear transformation appfied...
Leonardo Neumeyer, Mitch Weintraub