Thesis (MScIng)--University of Stellenbosch, 2004. / ENGLISH ABSTRACT: In this study the phoneme labels derived from a phoneme recogniser are used for phonetic
speaker recognition. The time-dependencies among phonemes are modelled by using
hidden Markov models (HMMs) for the speaker models. Experiments are done using firstorder
and second-order HMMs and various smoothing techniques are examined to address
the problem of data scarcity. The use of word labels for lexical speaker recognition is also
investigated. Single word frequencies are counted and the use of various word selections
as feature sets are investigated. During April 2004, the University of Stellenbosch, in collaboration
with Spescom DataVoice, participated in an international speaker verification
competition presented by the National Institute of Standards and Technology (NIST). The
University of Stellenbosch submitted phonetic and lexical (non-acoustic) speaker recognition
systems and a fused system (the primary system) that fuses the acoustic system of
Spescom DataVoice with the non-acoustic systems of the University of Stellenbosch. The
results were evaluated by means of a cost model. Based on the cost model, the primary
system obtained second and third position in the two categories that were submitted. / AFRIKAANSE OPSOMMING: Hierdie projek maak gebruik van foneem-etikette wat geklassifiseer word deur ’n foneemherkenner
en daarna gebruik word vir fonetiese sprekerherkenning. Die tyd-afhanklikhede
tussen foneme word gemodelleer deur gebruik te maak van verskuilde Markov modelle
(HMMs) as sprekermodelle. Daar word ge¨eksperimenteer met eerste-orde en tweede-orde
HMMs en verskeie vergladdingstegnieke word ondersoek om dataskaarsheid aan te spreek.
Die gebruik van woord-etikette vir sprekerherkenning word ook ondersoek. Enkelwoordfrekwensies
word getel en daar word ge¨eksperimenteer met verskeie woordseleksies as kenmerke
vir sprekerherkenning. Gedurende April 2004 het die Universiteit van Stellenbosch
in samewerking met Spescom DataVoice deelgeneem aan ’n internasionale sprekerverifikasie
kompetisie wat deur die National Institute of Standards and Technology (NIST)
aangebied is. Die Universiteit van Stellenbosch het ingeskryf vir ’n fonetiese en ’n woordgebaseerde
(nie-akoestiese) sprekerherkenningstelsel, asook ’n saamgesmelte stelsel wat as
primˆere stelsel dien. Die saamgesmelte stelsel is ’n kombinasie van Spescom DataVoice se
akoestiese stelsel en die twee nie-akoestiese stelsels van die Universiteit van Stellenbosch.
Die resultate is ge¨evalueer deur gebruik te maak van ’n koste-model. Op grond van die
koste-model het die primˆere stelsel tweede en derde plek behaal in die twee kategorie¨e
waaraan deelgeneem is.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/16315 |
| Date | 12 1900 |
| Creators | Du Toit, Ilze |
| Contributors | Du Preez, J. A., University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. |
| Publisher | Stellenbosch : University of Stellenbosch |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | Unknown |
| Type | Thesis |
| Format | xxiv, 187 leaves : ill. |
| Rights | University of Stellenbosch |
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