Sciweavers

111 search results - page 10 / 23
» Statistical Modeling for Unit Selection in Speech Synthesis
Sort
View
INTERSPEECH
2010
14 years 4 months ago
Autoregressive clustering for HMM speech synthesis
The autoregressive HMM has been shown to provide efficient parameter estimation and high-quality synthesis, but in previous experiments decision trees derived from a non-autoregre...
Matt Shannon, William Byrne
91
Voted
ICASSP
2011
IEEE
14 years 1 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...
ICASSP
2011
IEEE
14 years 1 months ago
Investigation of acoustic units for LVCSR systems
One important issue in designing state-of-the-art LVCSR systems is the choice of acoustic units. Context dependent (CD) phones remain the dominant form of acoustic units. They can...
Xunying Liu, Mark John Francis Gales, Jim L. Hiero...
ESANN
2000
14 years 11 months ago
A statistical model selection strategy applied to neural networks
In statistical modelling, an investigator must often choose a suitable model among a collection of viable candidates. There is no consensus in the research community on how such a...
Joaquín Pizarro Junquera, Elisa Guerrero V&...
ICPR
2006
IEEE
15 years 10 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...