Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

18

CSL
2016
Springer

favoriteEmaildiscussreport

62views Automated Reasoning» more CSL 2016»

Application of continuous state Hidden Markov Models to a classical problem in speech recognition

8 years 19 days ago

Application of continuous state Hidden Markov Models to a classical problem in speech recognition

Download www.birmingham.ac.uk

This paper describes an optimal algorithm using continuous state Hidden Markov Models for solving the HMS decoding problem, which is the problem of recovering an underlying sequence of phonetic units from measurements of smoothly varying acoustic features, thus inverting the speech generation process described by Holmes, Mattingly and Shearme in a well known paper (Speech synthesis by rule, Language and Speech 7 (1964)).

Colin J. Champion, S. M. Houghton

Real-time Traffic

Automated Reasoning | CSL 2016 |

claim paper

Related Content

» Variational nonparametric Bayesian Hidden Markov Model

» Large margin training for hidden Markov models with partially observed states

» A Parallel Phoneme Recognition Algorithm Based on Continuous Hidden Markov Model

» A multiresolution hidden Markov model using classspecific features

» An Empirical Exploration of Hidden Markov Models From Spelling Recognition to Speech Recog...

» The Application of Hidden Markov Models in Speech Recognition

» Factor analysed hidden Markov models for speech recognition

» Interpolating hidden Markov model and its application to automatic instrument recognition

» An EM Algorithm to Learn Sequences in the Wavelet Domain

» Generalized BaumWelch algorithm for discriminative training on large vocabulary continuous...

Post Info
More Details (n/a)

Added	01 Apr 2016
Updated	01 Apr 2016
Type	Journal
Year	2016
Where	CSL
Authors	Colin J. Champion, S. M. Houghton

Comments (0)