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» Two-Microphone Separation of Speech Mixtures
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IDA
2009
Springer
14 years 9 days ago
Underdetermined Instantaneous Audio Source Separation via Local Gaussian Modeling
Underdetermined source separation is often carried out by modeling time-frequency source coefficients via a fixed sparse prior. This approach fails when the number of active sourc...
Emmanuel Vincent, Simon Arberet, Rémi Gribo...
TASLP
2011
13 years 20 days 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
IJON
2008
116views more  IJON 2008»
13 years 5 months ago
Discovering speech phones using convolutive non-negative matrix factorisation with a sparseness constraint
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can ...
Paul D. O'Grady, Barak A. Pearlmutter
INTERSPEECH
2010
13 years 17 days 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
IDA
2009
Springer
14 years 9 days ago
Extension of Sparse, Adaptive Signal Decompositions to Semi-blind Audio Source Separation
Abstract. We apply sparse, fast and flexible adaptive lapped orthogonal transforms to underdetermined audio source separation using the time-frequency masking framework. This norm...
Andrew Nesbit, Emmanuel Vincent, Mark D. Plumbley