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Virginia Tech

Automatic Phoneme Recognition with Segmental Hidden Markov Models

Abstract

dc:description.abstract

A speaker independent continuous speech phoneme recognition and segmentation system is presented. We discuss the training and recognition phases of the phoneme recognition system as well as a detailed description of the integrated elements. The Hidden Markov Model (HMM) based phoneme models are trained using the Baum-Welch re-estimation procedure. Recognition and segmentation of the phonemes in the continuous speech is performed by a Segmental Viterbi Search on a Segmental Ergodic HMM for the phoneme states. We describe in detail the three phases of the phoneme joint recognition and segmentation system. First, the extraction of the Mel-Frequency Cepstral Coefficients (MFCC) and the corresponding Delta and Delta Log Power coefficients is described. Second, we describe the operation of the Baum-Welch re-estimation procedure for the training of the phoneme HMM models, including the K-Means and the Expectation-Maximization (EM) clustering algorithms used for the initialization of the Baum-Welch algorithm. Additionally, we describe the structural framework of - and the recognition procedure for - the ergodic Segmental HMM for the phoneme segmentation and recognition. We include test and simulation results for each of the individual systems integrated into the phoneme recognition system and finally for the phoneme recognition/segmentation system as a whole.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Electrical and Computer Engineering
Department dc:contributor.department
Electrical and Computer Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2010

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Baghdasaryan, Areg Gagik
Chair dc:contributor.committeechair
  • Beex, A. A. Louis
Committee members dc:contributor.committeemember
  • Wyatt, Christopher L.
  • da Silva, Claudio R. C. M.

Subjects

dc:subject × 7

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-02082010-174617
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/31182

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Baghdasaryan, Areg Gagik. Automatic Phoneme Recognition with Segmental Hidden Markov Models. masters thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/31182