Academic literature on the topic 'Text-independent speaker verification systems'

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Journal articles on the topic "Text-independent speaker verification systems"

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Rakhmanenko, I. A., A. A. Shelupanov, and E. Y. Kostyuchenko. "Automatic text-independent speaker verification using convolutional deep belief network." Computer Optics 44, no. 4 (2020): 596–605. http://dx.doi.org/10.18287/2412-6179-co-621.

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This paper is devoted to the use of the convolutional deep belief network as a speech feature extractor for automatic text-independent speaker verification. The paper describes the scope and problems of automatic speaker verification systems. Types of modern speaker verification systems and types of speech features used in speaker verification systems are considered. The structure and learning algorithm of convolutional deep belief networks is described. The use of speech features extracted from three layers of a trained convolution deep belief network is proposed. Experimental studies of the
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Shim, Hye-jin, Jee-weon Jung, Ju-ho Kim, and Ha-jin Yu. "Integrated Replay Spoofing-Aware Text-Independent Speaker Verification." Applied Sciences 10, no. 18 (2020): 6292. http://dx.doi.org/10.3390/app10186292.

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A number of studies have successfully developed speaker verification or presentation attack detection systems. However, studies integrating the two tasks remain in the preliminary stages. In this paper, we propose two approaches for building an integrated system of speaker verification and presentation attack detection: an end-to-end monolithic approach and a back-end modular approach. The first approach simultaneously trains speaker identification, presentation attack detection, and the integrated system using multi-task learning using a common feature. However, through experiments, we hypoth
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Auckenthaler, Roland, Michael Carey, and Harvey Lloyd-Thomas. "Score Normalization for Text-Independent Speaker Verification Systems." Digital Signal Processing 10, no. 1-3 (2000): 42–54. http://dx.doi.org/10.1006/dspr.1999.0360.

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Das, Rohan Kumar, and S. R. Mahadeva Prasanna. "Investigating Text-Independent Speaker Verification Systems Under Varied Data Conditions." Circuits, Systems, and Signal Processing 38, no. 8 (2019): 3778–801. http://dx.doi.org/10.1007/s00034-019-01028-x.

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Shahin, Ismail. "Employing Emotion Cues to Verify Speakers in Emotional Talking Environments." Journal of Intelligent Systems 25, no. 1 (2016): 3–17. http://dx.doi.org/10.1515/jisys-2014-0118.

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AbstractUsually, people talk neutrally in environments where there are no abnormal talking conditions such as stress and emotion. Other emotional conditions that might affect people’s talking tone include happiness, anger, and sadness. Such emotions are directly affected by the patient’s health status. In neutral talking environments, speakers can be easily verified; however, in emotional talking environments, speakers cannot be easily verified as in neutral talking ones. Consequently, speaker verification systems do not perform well in emotional talking environments as they do in neutral talk
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ZHAO, Jian, Yuan DONG, Xian-yu ZHAO, Hao YANG, and Hai-la WANG. "Cross similarity measurement for speaker adaptive test normalization in text-independent speaker verification." Journal of China Universities of Posts and Telecommunications 15, no. 2 (2008): 130–34. http://dx.doi.org/10.1016/s1005-8885(08)60097-7.

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Mariéthoz, Johnny, and Samy Bengio. "A kernel trick for sequences applied to text-independent speaker verification systems." Pattern Recognition 40, no. 8 (2007): 2315–24. http://dx.doi.org/10.1016/j.patcog.2007.01.011.

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Mao, Hongwei, Yan Shi, Yue Liu, Linqiang Wei, Yijie Li, and Yanhua Long. "Short-time speaker verification with different speaking style utterances." PLOS ONE 15, no. 11 (2020): e0241809. http://dx.doi.org/10.1371/journal.pone.0241809.

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In recent years, great progress has been made in the technical aspects of automatic speaker verification (ASV). However, the promotion of ASV technology is still a very challenging issue, because most technologies are still very sensitive to new, unknown and spoofing conditions. Most previous studies focused on extracting target speaker information from natural speech. This paper aims to design a new ASV corpus with multi-speaking styles and investigate the ASV robustness to these different speaking styles. We first release this corpus in the Zenodo website for public research, in which each s
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Zhang, Y., X. Zhu, and D. Zhang. "Correction to A novel text-independent speaker verification method based on the global speaker model." IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 30, no. 6 (2000): 883. http://dx.doi.org/10.1109/tsmca.2000.895929.

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Shi, Yan, Juanjuan Zhou, Yanhua Long, Yijie Li, and Hongwei Mao. "Addressing Text-Dependent Speaker Verification Using Singing Speech." Applied Sciences 9, no. 13 (2019): 2636. http://dx.doi.org/10.3390/app9132636.

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The automatic speaker verification (ASV) has achieved significant progress in recent years. However, it is still very challenging to generalize the ASV technologies to new, unknown and spoofing conditions. Most previous studies focused on extracting the speaker information from natural speech. This paper attempts to address the speaker verification from another perspective. The speaker identity information was exploited from singing speech. We first designed and released a new corpus for speaker verification based on singing and normal reading speech. Then, the speaker discrimination was compa
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Dissertations / Theses on the topic "Text-independent speaker verification systems"

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Shou-Chun, Yin 1980. "Speaker adaptation in joint factor analysis based text independent speaker verification." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=100735.

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This thesis presents methods for supervised and unsupervised speaker adaptation of Gaussian mixture speaker models in text-independent speaker verification. The proposed methods are based on an approach which is able to separate speaker and channel variability so that progressive updating of speaker models can be performed while minimizing the influence of the channel variability associated with the adaptation recordings. This approach relies on a joint factor analysis model of intrinsic speaker variability and session variability where inter-session variation is assumed to result primarily fr
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PINHEIRO, Hector Natan Batista. "Verificação de locutores independente de texto: uma análise de robustez a ruído." Universidade Federal de Pernambuco, 2015. https://repositorio.ufpe.br/handle/123456789/18045.

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Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2016-11-08T19:13:18Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Final.pdf: 15901621 bytes, checksum: e3bd1c1be70941932d970f61be02e4c1 (MD5)<br>Made available in DSpace on 2016-11-08T19:13:18Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_Final.pdf: 15901621 bytes, checksum: e3bd1c1be70941932d970f61be02e4c1 (MD5) Previous issue date: 2015-02-25<br>O processo de identificação de um determinado indivíduo
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Auckenthaler, R. W. "Text-independent speaker verification with limited resources." Thesis, Swansea University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.635810.

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Access to data or secure areas today requires verification of the person's identity. This is commonly performed by entering the PIN, a publicly unknown personal identification number. A person must remember this PIN and access is denied when a wrong number is entered or the number is forgotten. The PIN can also accidentally become known to the public domain. Then every person is able to access the private information. Biological characteristics of a person are used in future applications for the purpose of verification. These "biometrics" increase the convenience of the system and can lead to
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Mariéthoz, Johnny Paugam-Moisy Hélène. "Discriminant models for text-independent speaker verification." Lyon : Université Lumière Lyon 2, 2006. http://theses.univ-lyon2.fr/sdx/theses/lyon2/2006/mariethoz_j.

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Longworth, Chris. "Kernel methods for text-independent speaker verification." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608599.

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Uzuner, Halil. "Robust text-independent speaker recognition over telecommunications systems." Thesis, University of Surrey, 2006. http://epubs.surrey.ac.uk/843391/.

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Biometric recognition methods, using human features such as voice, face or fingeorprints, are increasingly popular for user authentication. Voice is unique in that it is a non-intrusive biometric which can be transmitted over the existing telecommunication networks, thereby allowing remote authentication. Current spealcer recognition systems can provide high recognition rates on clean speech signals. However, their performance has been shown to degrade in real-life applications such as telephone banking, where speech compression and background noise can affect the speech signal. In this work,
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Skosan, Marshalleno. "Histogram equalization for robust text-independent speaker verification in telephone environments." Master's thesis, University of Cape Town, 2005. http://hdl.handle.net/11427/5103.

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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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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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El, Hannani Asmaa. "Text-independent speaker verification based on high-level information extracted with data-driven methods." Evry, Institut national des télécommunications, 2007. http://www.theses.fr/2007TELE0009.

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Cette thèse s’inscrit dans le cadre de la vérification du locuteur qui vise à authentifier l’identité proclamée par le locuteur. La parole contient deux types d’informations caractérisant l’identité du locuteur. Le premier type (bas-niveau) reflète les propriétés spectrales de la parole qui sont liées à la structure physique de l’appareil vocal, alors que le deuxième type d’information (haut-niveau) reflète les traits comportementaux tels que la prosodie, l’information phonétique, la prononciation, l’utilisation idiolectale de mots, les paternes conversationnels, etc. Récemment, diverses étude
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Books on the topic "Text-independent speaker verification systems"

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Meisel, William S. The telephony voice user interface: Applications of speech recognition, text-to-speech, and speaker verification over the telephone. TMA Associates, 1998.

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Book chapters on the topic "Text-independent speaker verification systems"

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Hannani, Asmaa El, Dijana Petrovska-Delacrétaz, Benoît Fauve, et al. "Text-independent Speaker Verification." In Guide to Biometric Reference Systems and Performance Evaluation. Springer London, 2009. http://dx.doi.org/10.1007/978-1-84800-292-0_7.

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Ganchev, Todor, Nikos Fakotakis, and George Kokkinakis. "Text-Independent Speaker Verification: The WCL-1 System." In Text, Speech and Dialogue. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39398-6_37.

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Lu, Xiaochun, and Junxun Yin. "A Text-Independent Speaker Verification System Based on Cross Entropy." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04962-0_48.

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Sohafi-Bonab, Javad, and Mehdi Hosseinzadeh Aghdam. "Retracted: Feature Selection Using Ant Colony Optimization for Text-Independent Speaker Verification System." In Advances in Computation and Intelligence. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16493-4_2.

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Sohafi-Bonab, Javad, and Mehdi Hosseinzadeh Aghdam. "Erratum: Feature Selection Using Ant Colony Optimization for Text-Independent Speaker Verification System." In Advances in Computation and Intelligence. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16493-4_54.

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Nemati, Shahla, Reza Boostani, and Mohammad Davarpanah Jazi. "Retracted: A Novel Text-Independent Speaker Verification System Using Ant Colony Optimization Algorithm." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69905-7_48.

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Nemati, Shahla, Reza Boostani, and Mohammad Davarpanah Jazi. "Erratum: A Novel Text-Independent Speaker Verification System Using Ant Colony Optimization Algorithm." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69905-7_71.

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Rahman, Md Masudur, Sk Arifuzzaman Pranto, Romana Rahman Ema, Farheen Anfal, and Tajul Islam. "Application of Noise Reduction Techniques to Improve Speaker Verification to Multi-Speaker Text-to-Speech Input." In Advances in Intelligent Systems and Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2594-7_4.

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Sánchez-Soto, Eduardo, Marc Sigelle, and Gérard Chollet. "Graphical Models for Text-Independent Speaker Verification." In Nonlinear Speech Modeling and Applications. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11520153_26.

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Padrta, Aleš, and Jan Vaněk. "Introduction of Improved UWB Speaker Verification System." In Text, Speech and Dialogue. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11551874_47.

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Conference papers on the topic "Text-independent speaker verification systems"

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Balian, Julien, Raffaele Tavarone, Mathieu Poumeyrol, and Alice Coucke. "Small Footprint Text-Independent Speaker Verification For Embedded Systems." In ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2021. http://dx.doi.org/10.1109/icassp39728.2021.9413564.

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Ramou, Naim, Mustapha Djeddou, and Mhania Guerti. "Two classifiers score fusion for text independent speaker verification." In 2011 11th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2011. http://dx.doi.org/10.1109/isda.2011.6121778.

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Varchol, Peter, Dusan Levicky, and Jozef Juhar. "Optimalization of GMM for Text Independent Speaker Verification System." In 2008 18th International Conference Radioelektronika. IEEE, 2008. http://dx.doi.org/10.1109/radioelek.2008.4542690.

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Mohammadi, Mohsen, and Hamid Reza Sadegh Mohammadi. "Weighted I-Vector Based Text-Independent Speaker Verification System." In 2019 27th Iranian Conference on Electrical Engineering (ICEE). IEEE, 2019. http://dx.doi.org/10.1109/iraniancee.2019.8786420.

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Pinheiro, Hector N. B., Tsang Ing Ren, George D. C. Cavalcanti, Tsang Ing Jyh, and Jan Sijbers. "Type-2 Fuzzy GMM-UBM for Text-Independent Speaker Verification." In 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013). IEEE, 2013. http://dx.doi.org/10.1109/smc.2013.738.

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Kashani, Hamidreza Baradaran, Shaghayegh Reza, and Iman Sarraf Rezaei. "On Metric-based Deep Embedding Learning for Text-Independent Speaker Verification." In 2020 6th Iranian Conference on Signal Processing and Intelligent Systems (ICSPIS). IEEE, 2020. http://dx.doi.org/10.1109/icspis51611.2020.9349565.

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Das, Rohan Kumar, and S. R. Mahadeva Prasanna. "Investigating Text-independent Speaker Verification from Practically Realizable System Perspective." In 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2018. http://dx.doi.org/10.23919/apsipa.2018.8659567.

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Kang, Woo Hyun, and Nam Soo Kim. "Team02 Text-Independent Speaker Verification System for SdSV Challenge 2021." In Interspeech 2021. ISCA, 2021. http://dx.doi.org/10.21437/interspeech.2021-249.

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Li, Yin-Guo, Qin Wei, Thomas Fang Zheng, and Yang-Rui Yang. "Multi-layered Features with SVM for Text-independent Speaker Verification." In 2012 International Conference on Computer Science and Service System (CSSS). IEEE, 2012. http://dx.doi.org/10.1109/csss.2012.101.

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Hannani, Asmaa El, and Dijana Petrovska-Delacrétaz. "Fusing acoustic, phonetic and data-driven systems for text-independent speaker verification." In Interspeech 2007. ISCA, 2007. http://dx.doi.org/10.21437/interspeech.2007-153.

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