Proceedings ArticleDOI
Using hidden Markov models based on autoregressive principles for isolated word recognition
E.I. Bovbel,Polina P. Tkachova,Igor E. Kheidorov +2 more
- Vol. 3720, pp 434-443
TLDR
The developed autoregressive hidden Markov model and introduced speech character vector provide a very high recognition performance in the isolated words recognition task.Citations
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Book ChapterDOI
Belarussian Speech Recognition Using Genetic Algorithms
TL;DR: A program model is constructed which implements the technology of speech recognition using genetic algorithms and achieves optimal results with a database of separated Belarussian words.
References
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Book
Fundamentals of speech recognition
TL;DR: This book presents a meta-modelling framework for speech recognition that automates the very labor-intensive and therefore time-heavy and therefore expensive and expensive process of manually modeling speech.
Book
Connectionist Speech Recognition: A Hybrid Approach
Hervé Bourlard,Nelson Morgan +1 more
TL;DR: Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state-of-the-art continuous speech recognition systems based on Hidden Markov Models (HMMs) to improve their performance.
Journal ArticleDOI
Mixture autoregressive hidden Markov models for speech signals
TL;DR: The signal modeling methodology is discussed and experimental results on speaker independent recognition of isolated digits are given and the potential use of the modeling technique for other applications are discussed.
Journal ArticleDOI
2-D arithmetic Fourier transform using the Bruns method
TL;DR: A VLSI architecture is suggested for the proposed two-dimensional AFT algorithm based upon Bruns' method, which provides a more balanced scheme of computation of the even and odd coefficients of a Fourier series.