Rayleigh Mixture Model-Based Hidden Markov Modeling and Estimation of Noise in Noisy Speech Signals

Autor: Soren Vang Andersen, Karsten Vandborg Sørensen

Publikováno v: Sørensen, K V & Andersen, S V 2007, ' Rayleigh Mixture Model-Based Hidden Markov Modeling and Estimation of Noise in Noisy Speech Signals ', IEEE Transactions on Audio Speech and Language Processing, vol. 15, no. 3, pp. 901-917 . https://doi.org/10.1109/TASL.2006.885240

In this paper, we propose a new statistical model for noise periodogram modeling and estimation. The proposed model is a hidden Markov model (HMM) with a Rayleigh mixture model (RMM) in each state. For this new model, we derive an expectation-maximiz

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d9b8dd760ff5d4e7db67b2440131edb7
https://doi.org/10.1109/tasl.2006.885240

Hidden Markov Modeling of Noise Periodograms Using Rayleigh Mixture Models

Autor: Soren Vang Andersen, Karsten Vandborg Sørensen

Publikováno v: Sørensen, K V & Andersen, S V 2005, ' Hidden Markov Modeling of Noise Periodograms Using Rayleigh Mixture Models ', Paper presented at Asilomar Conference on Signals, Systems, and Computers, October 30-November 2, 2005, ASILOMAR Hotel and Conference Grounds, Pacific Grove, California, USA, United States, 19/05/2010 .

In this paper, we derive an Expectation-Maximization algorithm for hidden Markov models (HMMs) with a multivariate Rayleigh mixture model (RMM) in each state. We compare the use of multivariate RMMs to multivariate Gaussian mixture models in the gene

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3295fb6499dc331aa74934c35d93e43c
https://vbn.aau.dk/da/publications/7fb35690-a55e-11db-b8eb-000ea68e967b