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TASLP
2002
109views more  TASLP 2002»
13 years 4 months ago
Particle methods for Bayesian modeling and enhancement of speech signals
This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modeling and enhancement. The stochastic evolution mod...
Jaco Vermaak, Christophe Andrieu, Arnaud Doucet, S...
IJCNN
2006
IEEE
13 years 11 months ago
Rao-Blackwellized Particle Filtering for Sequential Speech Enhancement
— In this paper we present a method of sequential speech enhancement, where we infer clean speech signal using a Rao-Blackwellized particle filter (RBPF), given a noisecontamina...
Sunho Park, Seungjin Choi
ICASSP
2009
IEEE
13 years 11 months ago
On the use of Bayesian modeling for predicting noise reduction performance
In speech enhancement applications, a validated metric of noise reduction performance is vital in the relative ranking of noise reduction algorithms and in enhancing the performan...
Nazanin Pourmand, David Suelzle, Vijay Parsa, Yi H...
TASLP
2010
117views more  TASLP 2010»
12 years 11 months ago
Speech Enhancement Using Gaussian Scale Mixture Models
This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the fr...
Jiucang Hao, Te-Won Lee, Terrence J. Sejnowski
ICASSP
2010
IEEE
13 years 5 months ago
Statistical approach to enhancing esophageal speech based on Gaussian mixture models
This paper presents a novel method of enhancing esophageal speech using statistical voice conversion. Esophageal speech is one of the alternative speaking methods for laryngectome...
Hironori Doi, Keigo Nakamura, Tomoki Toda, Hiroshi...