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» Speech Enhancement Using Gaussian Scale Mixture Models
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TASLP
2011
14 years 6 months ago
A Probabilistic Interaction Model for Multipitch Tracking With Factorial Hidden Markov Models
—We present a simple and efficient feature modeling approach for tracking the pitch of two simultaneously active speakers. We model the spectrogram features of single speakers u...
Michael Wohlmayr, Michael Stark, Franz Pernkopf
INTERSPEECH
2010
14 years 6 months ago
Canonical state models for automatic speech recognition
Current speech recognition systems are often based on HMMs with state-clustered Gaussian Mixture Models (GMMs) to represent the context dependent output distributions. Though high...
Mark J. F. Gales, Kai Yu
ICPR
2004
IEEE
16 years 26 days ago
Learning Spatial Context from Tracking using Penalised Likelihoods
MAP estimation of Gaussian mixtures through maximisation of penalised likelihoods was used to learn models of spatial context. This enabled prior beliefs about the scale, orientat...
Hammadi Nait-Charif, Stephen J. McKenna
ICASSP
2008
IEEE
15 years 6 months ago
Video denoising using a spatiotemporal statistical model of wavelet coefficients
We propose a video denoising algorithm based on a spatiotemporal Gaussian scale mixture (ST-GSM) model in the wavelet transform domain. This model simultaneously captures local co...
Gijesh Varghese, Zhou Wang
ICMCS
2006
IEEE
129views Multimedia» more  ICMCS 2006»
15 years 5 months ago
Speaker Identification using a Microphone Array and a Joint HMM with Speech Spectrum and Angle of Arrival
In this paper, we present a speaker identification algorithm for a microphone array based on a first-order joint Hidden Markov Model (HMM) where the observations correspond to t...
Jack W. Stokes, John C. Platt, Sumit Basu