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» Simplifying Mixture Models Using the Unscented Transform
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COLT
2010
Springer
13 years 5 months ago
Toward Learning Gaussian Mixtures with Arbitrary Separation
In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Mikhail Belkin, Kaushik Sinha
ICIP
1998
IEEE
14 years 9 months ago
Adaptive Wavelet Packet Image Coding using an Estimation-Quantization Framework
In this paper, we extend the statistical model-based Estimation-Quantization (EQ) wavelet image coding algorithm introduced in [?] to include an adaptive transform component. For ...
Kannan Ramchandran, Mehmet Kivanç Mih&ccedi...
ICASSP
2009
IEEE
14 years 2 months ago
Voice conversion using Artificial Neural Networks
In this paper, we propose to use Artificial Neural Networks (ANN) for voice conversion. We have exploited the mapping abilities of ANN to perform mapping of spectral features of ...
Srinivas Desai, E. Veera Raghavendra, B. Yegnanara...
EMNLP
2007
13 years 9 months ago
What is the Jeopardy Model? A Quasi-Synchronous Grammar for QA
This paper presents a syntax-driven approach to question answering, specifically the answer-sentence selection problem for short-answer questions. Rather than using syntactic fea...
Mengqiu Wang, Noah A. Smith, Teruko Mitamura
INTERSPEECH
2010
13 years 2 months 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