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Relevant bibliographies by topics / Speaker identification system / Dissertations / Theses

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Dissertations / Theses on the topic 'Speaker identification system'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Hubeika, Valiantsina. "Intersession Variability Compensation in Language and Speaker Identification." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2008. http://www.nusl.cz/ntk/nusl-235432.

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Variabilita kanálu a hovoru je velmi důležitým problémem v úloze rozpoznávání mluvčího. V současné době je ve velkém množství vědeckých článků uvedeno několik technik pro kompenzaci vlivu kanálu. Kompenzace vlivu kanálu může být implementována jak v doméně modelu, tak i v doménách příznaků i skóre. Relativně nová výkoná technika je takzvaná eigenchannel adaptace pro GMM (Gaussian Mixture Models). Mevýhodou této metody je nemožnost její aplikace na jiné klasifikátory, jako napřílad takzvané SVM (Support Vector Machines), GMM s různým počtem Gausových komponent nebo v rozpoznávání řeči s použití

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2

Mtibaa, Aymen. "Towards robust and privacy-preserving speaker verification systems." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS002.

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Les systèmes de vérification du locuteur sont une technologie clé dans de nombreux appareils et services tels que les smartphones, les assistants numériques intelligents et les applications bancaires. Pendant la pandémie de COVID-19, les systèmes de contrôle d'accès basés sur des lecteurs d'empreintes digitales ou des claviers augmentent le risque de propagation du virus. Par conséquent, les entreprises repensent maintenant leurs systèmes de contrôle d'accès des employés et envisagent des technologies d'autorisation sans contact, telles que les systèmes de vérification des locuteurs. Cependant

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3

Wildermoth, Brett Richard, and n/a. "Text-Independent Speaker Recognition Using Source Based Features." Griffith University. School of Microelectronic Engineering, 2001. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20040831.115646.

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Speech signal is basically meant to carry the information about the linguistic message. But, it also contains the speaker-specific information. It is generated by acoustically exciting the cavities of the mouth and nose, and can be used to recognize (identify/verify) a person. This thesis deals with the speaker identification task; i.e., to find the identity of a person using his/her speech from a group of persons already enrolled during the training phase. Listeners use many audible cues in identifying speakers. These cues range from high level cues such as semantics and linguistics of the sp

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4

Wildermoth, Brett Richard. "Text-Independent Speaker Recognition Using Source Based Features." Thesis, Griffith University, 2001. http://hdl.handle.net/10072/366289.

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Speech signal is basically meant to carry the information about the linguistic message. But, it also contains the speaker-specific information. It is generated by acoustically exciting the cavities of the mouth and nose, and can be used to recognize (identify/verify) a person. This thesis deals with the speaker identification task; i.e., to find the identity of a person using his/her speech from a group of persons already enrolled during the training phase. Listeners use many audible cues in identifying speakers. These cues range from high level cues such as semantics and linguistics of the sp

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5

Phythian, Mark. "Speaker identification for forensic applications." Thesis, Queensland University of Technology, 1998. https://eprints.qut.edu.au/36079/3/__qut.edu.au_Documents_StaffHome_StaffGroupR%24_rogersjm_Desktop_36079_Digitised%20Thesis.pdf.

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A major application of Speaker Identification (SI) is suspect identification by voice. This thesis investigates techniques that can be used to improve SI technology as applied to suspect identification. Speech Coding techniques have become integrated into many of our modern voice communications systems. This prompts the question - how are automatic speaker identification systems and modern forensic identification techniques affected by the introduction of digitally coded speech channels? Presented in this thesis are three separate studies investigating the effects of speech coding and compres

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6

Chan, Siu Man. "Improved speaker verification with discrimination power weighting /." View abstract or full-text, 2004. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202004%20CHANS.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004.<br>Includes bibliographical references (leaves 86-93). Also available in electronic version. Access restricted to campus users.

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7

Cohen, Zachary Gideon. "Noise Reduction with Microphone Arrays for Speaker Identification." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/884.

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The presence of acoustic noise in audio recordings is an ongoing issue that plagues many applications. This ambient background noise is difficult to reduce due to its unpredictable nature. Many single channel noise reduction techniques exist but are limited in that they may distort the desired speech signal due to overlapping spectral content of the speech and noise. It is therefore of interest to investigate the use of multichannel noise reduction algorithms to further attenuate noise while attempting to preserve the speech signal of interest. Specifically, this thesis looks to investigate th

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8

Al-Ani, Ahmed Karim. "An improved pattern classification system using optimal feature selection, classifier combination, and subspace mapping techniques." Thesis, Queensland University of Technology, 2002.

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9

Gedik, Berk. "Evaluation of Text-Independent and Closed-Set Speaker Identification Systems." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-239625.

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Speaker recognition is the task of recognizing a speaker of a given speech record and it has wide application areas. In this thesis, various machine learning models such as Gaussian Mixture Model (GMM), k-Nearest Neighbor(k-NN) Model and Support Vector Machines (SVM) and feature extraction methods such as Mel-Frequency Cepstral Coefficients (MFCC) and Linear Predictive Cepstral Coefficients (LPCC) are investigated for the speaker recognition task. Combinations of those models and feature extraction methods are evaluated on many datasets varying on the number of speakers and training data size.

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10

Reynolds, Douglas A. "A Gaussian mixture modeling approach to text-independent speaker identification." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/16903.

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11

Al-Kaltakchi, Musab Tahseen Salahaldeen. "Robust text independent closed set speaker identification systems and their evaluation." Thesis, University of Newcastle upon Tyne, 2018. http://hdl.handle.net/10443/3978.

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This thesis focuses upon text independent closed set speaker identi cation. The contributions relate to evaluation studies in the presence of various types of noise and handset e ects. Extensive evaluations are performed on four databases. The rst contribution is in the context of the use of the Gaussian Mixture Model-Universal Background Model (GMM-UBM) with original speech recordings from only the TIMIT database. Four main simulations for Speaker Identi cation Accuracy (SIA) are presented including di erent fusion strategies: Late fusion (score based), early fusion (feature based) and early-

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12

Leis, John W. "Spectral coding methods for speech compression and speaker identification." Thesis, Queensland University of Technology, 1998. https://eprints.qut.edu.au/36062/7/36062_Digitised_Thesis.pdf.

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This thesis investigates aspects of encoding the speech spectrum at low bit rates, with extensions to the effect of such coding on automatic speaker identification. Vector quantization (VQ) is a technique for jointly quantizing a block of samples at once, in order to reduce the bit rate of a coding system. The major drawback in using VQ is the complexity of the encoder. Recent research has indicated the potential applicability of the VQ method to speech when product code vector quantization (PCVQ) techniques are utilized. The focus of this research is the efficient representation, calcu

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13

Castellano, Pierre John. "Speaker recognition modelling with artificial neural networks." Thesis, Queensland University of Technology, 1997.

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14

Wark, Timothy J. "Multi-modal speech processing for automatic speaker recognition." Thesis, Queensland University of Technology, 2001.

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15

Slomka, Stefan. "Multiple classifier structures for automatic speaker recognition under adverse conditions." Thesis, Queensland University of Technology, 1999.

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16

Barger, Peter James. "Speech processing for forensic applications." Thesis, Queensland University of Technology, 1998. https://eprints.qut.edu.au/36081/1/36081_Barger_1998.pdf.

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This thesis examines speech processing systems appropriate for use in forensic analysis. The need for automatic speech processing systems for forensic use is justified by the increasing use of electronically recorded speech for communication. An automatic speaker identification and verification system is described which was tested on data gathered by the Queensland Police Force. Speaker identification using Gaussian mixture models (GMMs) is shown to be useful as an indicator of identity, but not sufficiently accurate to be used as the sole means of identification. It is shown that training G

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17

Lucey, Simon. "Audio-visual speech processing." Thesis, Queensland University of Technology, 2002. https://eprints.qut.edu.au/36172/7/SimonLuceyPhDThesis.pdf.

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Speech is inherently bimodal, relying on cues from the acoustic and visual speech modalities for perception. The McGurk effect demonstrates that when humans are presented with conflicting acoustic and visual stimuli, the perceived sound may not exist in either modality. This effect has formed the basis for modelling the complementary nature of acoustic and visual speech by encapsulating them into the relatively new research field of audio-visual speech processing (AVSP). Traditional acoustic based speech processing systems have attained a high level of performance in recent years, but the p

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18

Lin, Guan-Liang, and 林冠良. "An MFCC-based Speaker Identification System." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/fx7824.

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碩士<br>東海大學<br>資訊工程學系<br>105<br>Nowadays, speech recognition has many practical applications which are currently used by people in the world. Typical examples are the SIRI of iPhone, Google speech recognition system, and mobile phones operated by voice, etc. On the contrary, speaker identification in its current stage is relatively immature. Therefore, in this paper, we study a speaker identification technique which first takes the original voice signals of a person, e.g., Bob. After that, the voice signals is converted from time domain to frequency domain by employing the Fourier transformatio

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19

Lyu, Yi-Chen, and 呂易宸. "Speech Access System based on Speaker Identification." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/49174049479521734264.

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碩士<br>國立中央大學<br>電機工程研究所<br>99<br>The purpose of this thesis is to design a speech access system with speaker recognition technology which can determine whether the input sound of the user voice is valid or not. Combined with keywords spotting technology, the system can identify the name of users. And coupled with text-to-speech technology, the system uses not only a text but also human voice response. System built by Microsoft Foundation Classes (MFC) windows based interface is facilitated for the user to operate. Because access control system needs to meet the requirements of real-time or

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20

Yu, Ming-Der, and 于明德. "A Design of Text Independent Speaker Identification System for Telephone Speech." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/48072274198405347870.

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碩士<br>國立中山大學<br>電機工程研究所<br>85<br>A Text independent speaker identification system based on long-term spectral feature averaging (LTA) and Karhunen-Loeve transform (KLT) for telephone speech is proposed. This system uses basis function derived from KLT to effectively reduce the data volume and preserve most of the identification information for each speaker. A database with 61 male and 72 female mandarin speakers recorded from the telephone answering system are collected for system evaluation. By the use of the first 28 features from the 128 basis functions, it is demonstrated that the corre

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21

CHIANG, CHANG YEN, and 蔣昌言. "Text-Independent Speaker Identification System Based on Karhunen-Loeve Transform and Quadratic Classifier." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/19284077261651106741.

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22

Tsai, Zong-Syuan, and 蔡宗軒. "Speaker Identification System based on Long Term Average Spectrum and Speech Content Distribution." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/10322757746063947883.

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碩士<br>國立臺灣大學<br>電機工程學研究所<br>100<br>Timbre is the important characteristic that human can distinguish the difference between each other by their voice. This thesis aims to give a feature of timbre that considers both Long Term Average Spectrum (LTAS) and speech content distribution and implements to speaker identification system. LTAS is a feature influenced by both characteristics of speaker and content, so the same speaker still has inconsistent patterns of LTAS. The inconsistency of patterns also directly influences the accuracy of speaker identification using LTAS as feature. To increas

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23

Sanchez, Jose Boris Meyer-Baese Anke. "Speaker identification based on an integrated system combining cepstral feature extraction and vector quantization." Diss., 2005. http://etd.lib.fsu.edu/theses/available/etd-04172005-151234.

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Thesis (M.S.)--Florida State University, 2005.<br>Advisor: Dr. Anke Meyer-Baese, Florida State University, College of Engineering, Dept. of Electrical Engineering. Title and description from dissertation home page (viewed June 15, 2005). Document formatted into pages; contains vii, 30 pages. Includes bibliographical references.

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24

古詩峰. "A Large Population Speaker Identification System Based on Wavelet Transform Features by Using Microphone and Telephone Speech Corpus." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/54547071414963915299.

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碩士<br>長庚大學<br>電機工程研究所<br>91<br>In this thesis, we have established a large population speaker identification system which is based on Gaussian Mixture Models using wavelet based features. The corpus for experiments of this thesis are the well-known TIMIT phonetically balance speech database for microphone speech (TIMIT) and a new collected Formosa Speech Corpus for telephone speech (FSC-Tel 1000). We achieve the best speaker accuracy of 99.127% for TIMIT corpus and 95.5% for FSC-Tel 1000 corpus. About wavelet based features, our objective is to found a suitable wavelet decomposing t

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25

Huang, Hung-Pin, and 黃紘斌. "Robust Speaker Identification Systems against Additive Noise and Reverberation." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/82731413646820206152.

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碩士<br>國立交通大學<br>電信工程研究所<br>100<br>Conventional speaker recognition systems usually use MFCCs as features, which are known as low-level features and the performance are severely compromised by interference, such as additive or convolutional noises. On the contrary, the high-level features seemed to be less accuracy in clean condition but more robustness in noisy environment. In this thesis, we first pass the speech wave thorough the hearing models, then choose 9 sets of outputs after spectro-temporal modulation filtering as our features and apply those features for robust speaker recognition. T

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26

Mohan, Aanchan K. "Combining speech recognition and speaker verification." 2008. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.17528.

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