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» State Duration Modeling for HMM-Based Speech Synthesis
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BMCBI
2007
98views more  BMCBI 2007»
13 years 5 months ago
Duration learning for analysis of nanopore ionic current blockades
Background: Ionic current blockade signal processing, for use in nanopore detection, offers a promising new way to analyze single molecule properties, with potential implications ...
Alexander G. Churbanov, Carl Baribault, Stephen Wi...
NAACL
2003
13 years 6 months ago
Implicit Trajectory Modeling through Gaussian Transition Models for Speech Recognition
It is well known that frame independence assumption is a fundamental limitation of current HMM based speech recognition systems. By treating each speech frame independently, HMMs ...
Hua Yu, Tanja Schultz
ICASSP
2011
IEEE
12 years 9 months ago
Discriminatively estimated discrete, parametric and smoothed-discrete duration models for speech recognition
Duration of phonemic segments provide important cues for distinguishing words in languages such as Arabic. Recently, we proposed a discriminatively estimated joint acoustic, durat...
Maider Lehr, Izhak Shafran
ICASSP
2011
IEEE
12 years 9 months ago
Utilizing glottal source pulse library for generating improved excitation signal for HMM-based speech synthesis
This paper describes a source modeling method for hidden Markov model (HMM) based speech synthesis for improved naturalness. A speech corpus is rst decomposed into the glottal sou...
Tuomo Raitio, Antti Suni, Hannu Pulakka, Martti Va...
IJCNN
2006
IEEE
13 years 11 months ago
Reservoir-based techniques for speech recognition
— A solution for the slow convergence of most learning rules for Recurrent Neural Networks (RNN) has been proposed under the terms Liquid State Machines (LSM) and Echo State Netw...
David Verstraeten, Benjamin Schrauwen, Dirk Stroob...