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» Melody Spotting Using Hidden Markov Models
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NIPS
2008
15 years 5 months ago
Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction
We explore a new Bayesian model for probabilistic grammars, a family of distributions over discrete structures that includes hidden Markov models and probabilistic context-free gr...
Shay B. Cohen, Kevin Gimpel, Noah A. Smith
INTERSPEECH
2010
14 years 11 months ago
Synthesis of fast speech with interpolation of adapted HSMMs and its evaluation by blind and sighted listeners
In this paper we evaluate a method for generating synthetic speech at high speaking rates based on the interpolation of hidden semi-Markov models (HSMMs) trained on speech data re...
Michael Pucher, Dietmar Schabus, Junichi Yamagishi
ICDAR
2009
IEEE
15 years 2 months ago
Stochastic Model of Stroke Order Variation
A stochastic model of stroke order variation is proposed and applied to the stroke-order free on-line Kanji character recognition. The proposed model is a hidden Markov model (HMM...
Yoshinori Katayama, Seiichi Uchida, Hiroaki Sakoe
ICASSP
2009
IEEE
15 years 11 months ago
Speech emotion recognition via a max-margin framework incorporating a loss function based on the Watson and Tellegen's emotion m
This paper considers a method for speech emotion recognition by a max-margin framework incorporating a loss function based on a well-known model called the Watson and Tellegen’s...
Sungrack Yun, Chang D. Yoo
ICGI
1994
Springer
15 years 8 months ago
Inducing Probabilistic Grammars by Bayesian Model Merging
We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are incorporated by adding ad-hoc rules to a working grammar; subseque...
Andreas Stolcke, Stephen M. Omohundro