Hidden Markov Independent Component Analysis

By W. D. Penny, Richard M. Everson, Stephen J. Roberts. 2000

34 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Patrick Kenny
2. Pierre Dumouchel
3. Hermanni Hälvä
4. Aapo Hyvärinen
5. Gilles Boulianne
6. Yoshua Bengio
7. Bernhard Schölkopf
8. Najim Dehak

In Cognitive Neuroscience

1. Patrick Kenny
2. Pierre Dumouchel
3. Aapo Hyvärinen
4. Gilles Boulianne
5. Yann LeCun
6. Kun Zhang
7. Urs Köster

In Signal Processing

1. Patrick Kenny
2. Pierre Dumouchel
3. Hermanni Hälvä
4. Aapo Hyvärinen
5. Gilles Boulianne
6. Najim Dehak
7. Bernhard Schölkopf
8. Yoshua Bengio

Citations in the corpus

• Hidden Markov Nonlinear ICA: Unsupervised Learning from Nonstationary Time Series (2020, background): “This idea has been proposed earlier for linear ICA (Penny et al., 2000; Zhou and Zhang, 2008) but their identifiability and estimation results do not directly extend to the nonlinear case.”
• Eigenvoice modeling with sparse training data (2005, methodology): “Integrating ICA with HMMs is straightforward in principle [ 24 ].) This suggests that non-Gaussian modeling of speaker supervectors could also be considered but we do not have any evidence to indicate whether this is worth pursuing.”