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- Mikkel N. Schmidt, Rasmus Kongsgaard Olsson
- INTERSPEECH
- 2006

We apply machine learning techniques to the problem of separating multiple speech sources from a single microphone recording. The method of choice is a sparse non-negative matrix factorizationâ€¦ (More)

- Rasmus Kongsgaard Olsson, Lars Kai Hansen
- 2004 12th European Signal Processing Conference
- 2004

We solve a class of blind signal separation problems using a constrained linear Gaussian model. The observed signal is modelled by a convolutive mixture of colored noise signals with additive whiteâ€¦ (More)

The number of source signals in a noisy convolutive mixture is determined based on the exact log-likelihoods of the candidate models. In (Olsson and Hansen, 2004), a novel probabilistic blind sourceâ€¦ (More)

- Rasmus Kongsgaard Olsson, Lars Kai Hansen
- NIPS
- 2004

We discuss an identification framework for noisy speech mixtures. A block-based generative model is formulated that explicitly incorporates the time-varying harmonic plus noise (H+N) model for aâ€¦ (More)

- Mikkel N. Schmidt, Rasmus Kongsgaard Olsson
- 2007 IEEE Workshop on Applications of Signalâ€¦
- 2007

In this work we address the problem of separating multiple speakers from a single microphone recording. We formulate a linear regression model for estimating each speaker based on features derivedâ€¦ (More)

- Rasmus Kongsgaard Olsson, Lars Kai Hansen
- 2006 IEEE International Conference on Acousticsâ€¦
- 2006

We demonstrate that blind separation of more sources than sensors can be performed based solely on the second order statistics of the observed mixtures. This generalization of well-known robustâ€¦ (More)

- Rasmus Kongsgaard Olsson, Lars Kai Hansen
- Journal of Machine Learning Research
- 2006

We apply a type of generative modelling to the problem of blind source separation in which prior knowledge about the latent source signals, such as time-varying auto-correlation and quasiperiodicity,â€¦ (More)

- Shoji Makino, Te-Won Lee, +4 authors Anthony M. Zador
- 2007

We explore the use of sparse representations for separation of a monaural mixture signal, where by a sparse representation we mean one where the number of non-zero elements is smaller than might beâ€¦ (More)

- Finn Eichhorn, Lasse Hogstedt, +4 authors Peter Uhd Jepsen
- 35th International Conference on Infraredâ€¦
- 2010

We report on a broadband multi-element THz imaging system based on fiber-coupled, integrated photoconductive emitters and detectors. 32 detectors and 32 emitters are arranged in a planar array.â€¦ (More)

In this work we address the problem of separating multiple speakers from a single microphone recording. We formulate a linear regression model for estimating each speaker based on features derivedâ€¦ (More)