Full Text Available

Note: Clicking the button above will open the full text document at the original institutional repository in a new window.

Non-acoustic speaker recognition

Thesis (MScIng)--University of Stellenbosch, 2004.

Saved in:
Bibliographic Details
Main Author: Du Toit, Ilze
Other Authors: Du Preez, J. A.
Format: Thesis
Language:en_ZA
Published: Stellenbosch : University of Stellenbosch 2011
Subjects:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1867613888897351680
access_status_str Open Access
author Du Toit, Ilze
author2 Du Preez, J. A.
author_browse Du Preez, J. A.
Du Toit, Ilze
author_facet Du Preez, J. A.
Du Toit, Ilze
author_sort Du Toit, Ilze
collection Thesis
dc_rights_str_mv University of Stellenbosch
description Thesis (MScIng)--University of Stellenbosch, 2004.
format Thesis
id oai:scholar.sun.ac.za:10019.1/16315
institution Stellenbosch University (South Africa)
language en_ZA
last_indexed 2026-06-10T12:43:18.087Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository
publishDate 2011
publishDateRange 2011
publishDateSort 2011
publisher Stellenbosch : University of Stellenbosch
publisherStr Stellenbosch : University of Stellenbosch
record_format dspace
source_str SUNScholar — Stellenbosch University Repository
spelling oai:scholar.sun.ac.za:10019.1/16315 Non-acoustic speaker recognition Du Toit, Ilze Du Preez, J. A. University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. Automatic speech recognition Speech processing systems Speech perception Theses -- Electronic engineering Dissertations -- Electronic engineering 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. 2011-08-29T10:56:48Z 2011-08-29T10:56:48Z 2004-12 Thesis http://hdl.handle.net/10019.1/16315 en_ZA University of Stellenbosch xxiv, 187 leaves : ill. application/pdf Stellenbosch : University of Stellenbosch
spellingShingle Automatic speech recognition
Speech processing systems
Speech perception
Theses -- Electronic engineering
Dissertations -- Electronic engineering
Du Toit, Ilze
Non-acoustic speaker recognition
title Non-acoustic speaker recognition
title_full Non-acoustic speaker recognition
title_fullStr Non-acoustic speaker recognition
title_full_unstemmed Non-acoustic speaker recognition
title_short Non-acoustic speaker recognition
title_sort non acoustic speaker recognition
topic Automatic speech recognition
Speech processing systems
Speech perception
Theses -- Electronic engineering
Dissertations -- Electronic engineering
url http://hdl.handle.net/10019.1/16315
work_keys_str_mv AT dutoitilze nonacousticspeakerrecognition