Non-acoustic speaker recognition
| dc.contributor.advisor | Du Preez, J. A. | |
| dc.contributor.author | Du Toit, Ilze | |
| dc.contributor.other | University of Stellenbosch. Faculty of Engineering. Dept. of Electrical and Electronic Engineering. | |
| dc.date.accessioned | 2011-08-29T10:56:48Z | |
| dc.date.available | 2011-08-29T10:56:48Z | |
| dc.date.issued | 2004-12 | |
| dc.description | Thesis (MScIng)--University of Stellenbosch, 2004. | en_ZA |
| dc.description.abstract | 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. | en_ZA |
| dc.description.abstract | 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. | af |
| dc.format.extent | xxiv, 187 leaves : ill. | |
| dc.identifier.uri | http://hdl.handle.net/10019.1/16315 | |
| dc.language.iso | en_ZA | en_ZA |
| dc.publisher | Stellenbosch : University of Stellenbosch | |
| dc.rights.holder | University of Stellenbosch | |
| dc.subject | Automatic speech recognition | en_ZA |
| dc.subject | Speech processing systems | en_ZA |
| dc.subject | Speech perception | en_ZA |
| dc.subject | Theses -- Electronic engineering | en_ZA |
| dc.subject | Dissertations -- Electronic engineering | en_ZA |
| dc.title | Non-acoustic speaker recognition | en_ZA |
| dc.type | Thesis | en_ZA |