Add to ORKGAbstract. Specifics of hidden Markov model-based speech recognition are investigated. Influ-ence of modeling simple and context-dependent phones, using simple Gaussian, two and three-component Gaussian mixture probability density functions for modeling feature distribution, and incorporating language model are discussed. Word recognition rates and model complexity criteria are used for evaluating suitability of these modifications for practical applications. Development of large vocabulary continuous speech recognition system using HTK toolkit and WSJCAM0 English speech corpus is described. Results of experimental investigations are presented. Key words: large vocabulary continuous speech recognition, hidden Markov model, Viterb
The purpose with this final master degree project was to develop a speech recognition tool, to make ...
A summary of the theory of the hybrid connectionist HMM (hidden Markov model) continuous speech reco...
We present a novel scheme for phoneme recognition in continuous speech using inhomogeneous hidden Ma...
Specifics of hidden Markov model-based speech recognition are investigated. Influence of modeling si...
This paper gives an overview of the principles of a system for phoneme based, large vocabulary, cont...
This work consists on designing a continuous speech recognition system using pattern recognition tec...
This thesis investigates a stochastic modeling approach to word hypothesis of phonetic strings for a...
Stochastic signal processing techniques have pro-foundly changed our perspective on speech processin...
HLT1994: Workshop on Human Language Technology , March 8-11, 1994, Plainsboro, New Jerey, USA.Thi...
Abstract: "A semi-continuous hidden Markov model based on multiple vector quantization codebooks is ...
In general the aim of an automatic speech recognition system is to write down what is said. State of...
In this paper the incorporation of important phonetic properties into hidden Markov models (HMM) is ...
Natural language processing enables computer and machines to understand and speak human languages. S...
Voice control is one of the perspective areas of interdisciplinary field called Human Machine Interf...
In this paper we address the problem of phoneme recognition in continuous speech using a two stage p...
The purpose with this final master degree project was to develop a speech recognition tool, to make ...
A summary of the theory of the hybrid connectionist HMM (hidden Markov model) continuous speech reco...
We present a novel scheme for phoneme recognition in continuous speech using inhomogeneous hidden Ma...
Specifics of hidden Markov model-based speech recognition are investigated. Influence of modeling si...
This paper gives an overview of the principles of a system for phoneme based, large vocabulary, cont...
This work consists on designing a continuous speech recognition system using pattern recognition tec...
This thesis investigates a stochastic modeling approach to word hypothesis of phonetic strings for a...
Stochastic signal processing techniques have pro-foundly changed our perspective on speech processin...
HLT1994: Workshop on Human Language Technology , March 8-11, 1994, Plainsboro, New Jerey, USA.Thi...
Abstract: "A semi-continuous hidden Markov model based on multiple vector quantization codebooks is ...
In general the aim of an automatic speech recognition system is to write down what is said. State of...
In this paper the incorporation of important phonetic properties into hidden Markov models (HMM) is ...
Natural language processing enables computer and machines to understand and speak human languages. S...
Voice control is one of the perspective areas of interdisciplinary field called Human Machine Interf...
In this paper we address the problem of phoneme recognition in continuous speech using a two stage p...
The purpose with this final master degree project was to develop a speech recognition tool, to make ...
A summary of the theory of the hybrid connectionist HMM (hidden Markov model) continuous speech reco...
We present a novel scheme for phoneme recognition in continuous speech using inhomogeneous hidden Ma...