Academic literature on the topic 'Speaker identification system'

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Journal articles on the topic "Speaker identification system"

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Aung, Zaw Win. "A Robust Speaker Identification System." International Journal of Trend in Scientific Research and Development Volume-2, Issue-5 (2018): 2057–64. http://dx.doi.org/10.31142/ijtsrd18274.

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Jayanna, H. S., and B. G. Nagaraja. "An Experimental Comparison of Modeling Techniques and Combination of Speaker – Specific Information from Different Languages for Multilingual Speaker Identification." Journal of Intelligent Systems 25, no. 4 (2016): 529–38. http://dx.doi.org/10.1515/jisys-2014-0128.

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AbstractMost of the state-of-the-art speaker identification systems work on a monolingual (preferably English) scenario. Therefore, English-language autocratic countries can use the system efficiently for speaker recognition. However, there are many countries, including India, that are multilingual in nature. People in such countries have habituated to speak multiple languages. The existing speaker identification system may yield poor performance if a speaker’s train and test data are in different languages. Thus, developing a robust multilingual speaker identification system is an issue in ma
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Kim, Kyung-Wha, Byung-Min So, and Ha-Jin Yu. "Forensic Automatic Speaker Identification System for Korean Speakers." Phonetics and Speech Sciences 4, no. 3 (2012): 95–101. http://dx.doi.org/10.13064/ksss.2012.4.3.095.

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Shah, Shahid Munir, Muhammad Moinuddin, and Rizwan Ahmed Khan. "A Robust Approach for Speaker Identification Using Dialect Information." Applied Computational Intelligence and Soft Computing 2022 (March 7, 2022): 1–16. http://dx.doi.org/10.1155/2022/4980920.

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The present research is an effort to enhance the performance of voice processing systems, in our case the speaker identification system (SIS) by addressing the variability caused by the dialectical variations of a language. We present an effective solution to reduce dialect-related variability from voice processing systems. The proposed method minimizes the system’s complexity by reducing search space during the testing process of speaker identification. The speaker is searched from the set of speakers of the identified dialect instead of all the speakers present in system training. The study
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Singh, Mahesh K., P. Mohana Satya, Vella Satyanarayana, and Sridevi Gamini. "Speaker Recognition Assessment in a Continuous System for Speaker Identification." International Journal of Electrical and Electronics Research 10, no. 4 (2022): 862–67. http://dx.doi.org/10.37391/ijeer.100418.

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This research article presented and focused on recognizing speakers through multi-speaker speeches. The participation of several speakers includes every conference, talk or discussion. This type of talk has different problems as well as stages of processing. Challenges include the unique impurity of the surroundings, the involvement of speakers, speaker distance, microphone equipment etc. In addition to addressing these hurdles in real time, there are also problems in the treatment of the multi-speaker speech. Identifying speech segments, separating the speaking segments, constructing clusters
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Zaw, Win Aung. "A Robust Speaker Identification System." International Journal of Trend in Scientific Research and Development 2, no. 5 (2018): 2057–64. https://doi.org/10.31142/ijtsrd18274.

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This paper is aimed to implement a robust speaker identification system. It is a software architecture which identifies the current talker out of a set of speakers. The system is emphasized on text dependent speaker identification system. It contains three main modules endpoint detection, feature extraction and feature matching. The additional module, endpoint detection, removes unwanted signal and background noise from the input speech signal before subsequent processing. In the proposed system, Short Term Energy analysis is used for endpoint detection. Mel frequency Cepstrum Coefficients MFC
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Mammone, Richard J. "Speaker identification and verification system." Journal of the Acoustical Society of America 101, no. 2 (1997): 665. http://dx.doi.org/10.1121/1.419408.

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Kleider, John Eric, and Khaled Assaleh. "Speaker identification system and method." Journal of the Acoustical Society of America 107, no. 6 (2000): 2952. http://dx.doi.org/10.1121/1.429392.

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Singh, Satyanand. "Forensic and Automatic Speaker Recognition System." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 2804. http://dx.doi.org/10.11591/ijece.v8i5.pp2804-2811.

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<span lang="EN-US">Current Automatic Speaker Recognition (ASR) System has emerged as an important medium of confirmation of identity in many businesses, ecommerce applications, forensics and law enforcement as well. Specialists trained in criminological recognition can play out this undertaking far superior by looking at an arrangement of acoustic, prosodic, and semantic attributes which has been referred to as structured listening. An algorithmbased system has been developed in the recognition of forensic speakers by physics scientists and forensic linguists to reduce the probability of
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EhKan, Phaklen, Timothy Allen, and Steven F. Quigley. "FPGA Implementation for GMM-Based Speaker Identification." International Journal of Reconfigurable Computing 2011 (2011): 1–8. http://dx.doi.org/10.1155/2011/420369.

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In today's society, highly accurate personal identification systems are required. Passwords or pin numbers can be forgotten or forged and are no longer considered to offer a high level of security. The use of biological features, biometrics, is becoming widely accepted as the next level for security systems. Biometric-based speaker identification is a method of identifying persons from their voice. Speaker-specific characteristics exist in speech signals due to different speakers having different resonances of the vocal tract. These differences can be exploited by extracting feature vectors su
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Dissertations / Theses on the topic "Speaker identification system"

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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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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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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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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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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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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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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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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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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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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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Books on the topic "Speaker identification system"

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Franz, Gerl, Minker Wolfgang, and SpringerLink (Online service), eds. Self-Learning Speaker Identification: A System for Enhanced Speech Recognition. Springer-Verlag Berlin Heidelberg, 2011.

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Sabourin, Conrad. Computational speech processing: Speech analysis, recognition, understanding, compression, transmission, coding, synthesis, text to speech systems, speech to tactile displays, speaker identification, prosody processing : bibliography. Infolingua, 1994.

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Herbig, Tobias, Franz Gerl, and Wolfgang Minker. Self-Learning Speaker Identification: A System for Enhanced Speech Recognition. Springer, 2013.

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Douds, Anne S., and Eileen M. Ahlin. Rethinking America’s Correctional Policies. The Rowman & Littlefield Publishing Group, 2017. https://doi.org/10.5040/9781978731509.

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Commonsense Choices from Uncommon Voices:Rethinking America’s Correctional Policies brings together the experiences of men who served time in prison with contemporary research on correctional policy. This work combines a voyeuristic desire to observe “evil” and the consequences of the system of punishment, with detached consideration of what those stories can tell us about who we are as a nation and how we treat those who have betrayed the social trust. The authors simultaneously examine first-person accounts of inmate experiences with the correctional system and what actually, works, in opera
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Johnson, Sarah Kathleen. Occasional Religious Practice. Oxford University PressNew York, NY, 2025. https://doi.org/10.1093/9780197806579.001.0001.

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Abstract Occasional religious practice is a way of relating to religion that is characterized by participation in religious practices occasionally rather than routinely, most often in connection with certain types of occasions, including holidays, life transitions, and times of crisis. Anchored in three years of ethnographic research in the Anglican tradition in Toronto, this interdisciplinary study employs qualitative theological methods to develop the concept of occasional religious practice. Sociologically, occasional religious practice is a consistent yet underdeveloped theme in research o
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Haslam, Nick. Reliability, Validity, and the Mixed Blessings of Operationalism. Edited by K. W. M. Fulford, Martin Davies, Richard G. T. Gipps, et al. Oxford University Press, 2013. http://dx.doi.org/10.1093/oxfordhb/9780199579563.013.0058.

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The concepts of reliability and validity are fundamental for evaluating psychiatric diagnosis, including the "operationalist" approach pioneered in DSM-III. This chapter explores the complexity of these psychometric concepts and their interrelations. Although reliability constrains validity it does not guarantee it, and pursuing reliability in diagnosis can reduce validity. It is widely believed that the operationalist emphasis on diagnostic reliability has compromised the validity of recent psychiatric classifications. In particular, writers have argued that the drive for atheoretical diagnos
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Book chapters on the topic "Speaker identification system"

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Herbig, Tobias, Franz Gerl, and Wolfgang Minker. "Unsupervised Speech Controlled System with Long-Term Adaptation." In Self-Learning Speaker Identification. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19899-1_5.

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Herbig, Tobias, Franz Gerl, and Wolfgang Minker. "Evolution of an Adaptive Unsupervised Speech Controlled System." In Self-Learning Speaker Identification. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19899-1_6.

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Kan, Phak Len Eh, Tim Allen, and Steven F. Quigley. "A GMM-Based Speaker Identification System on FPGA." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12133-3_34.

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Mukherjee, Himadri, Moumita Dutta, Sk Md Obaidullah, K. C. Santosh, Santanu Phadikar, and Kaushik Roy. "SISU - A Speaker Identification System from Short Utterances." In Communications in Computer and Information Science. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-9181-1_39.

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Ma, Xinjun, Chenchen Wu, Yuanyuan Li, and Qianyuan Zhong. "Speaker Identification System Based on Lip-Motion Feature." In Lecture Notes in Computer Science. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68345-4_26.

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Goel, Deeksha, Shreya Sharma, Pooja Gambhir, Kiran Malik, and Poonam Bansal. "Feature Extraction Analysis in a Speaker Identification System." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-60935-0_46.

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Rekik, Ahmed, Achraf Ben-Hamadou, and Walid Mahdi. "Unified System for Visual Speech Recognition and Speaker Identification." In Advanced Concepts for Intelligent Vision Systems. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25903-1_33.

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Saritha, Banala, Tungala Thiru Venkata Naga Manoj, Sachin Kumar Sharma, Rabul Hussain Laskar, Madhuchhanda Choudhury, and K. Anish Monsley. "Intelligent Speaker Identification System Under Multi-Variability Speech Conditions." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4713-3_35.

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Guffanti, Diego, Danilo Martínez, José Paladines, and Andrea Sarmiento. "Continuous Speech Recognition and Identification of the Speaker System." In Proceedings of the International Conference on Information Technology & Systems (ICITS 2018). Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73450-7_72.

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Biagetti, Giorgio, Paolo Crippa, Laura Falaschetti, Simone Orcioni, and Claudio Turchetti. "Distributed Speech and Speaker Identification System for Personalized Domotic Control." In Mobile Networks for Biometric Data Analysis. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39700-9_13.

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Conference papers on the topic "Speaker identification system"

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Bazyar, Mohsen, and Rubita Sudirman. "A new speaker change detection method in a speaker identification system for two-speakers segmentation." In 2014 IEEE Symposium on Computer Applications & Industrial Electronics (ISCAIE). IEEE, 2014. http://dx.doi.org/10.1109/iscaie.2014.7010226.

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Youssif, A. A., E. A. Sarhan, and W. H. El Behaidy. "Development of automatic speaker identification system." In Proceedings of the Twenty-First National Radio Science Conference. IEEE, 2004. http://dx.doi.org/10.1109/nrsc.2004.240502.

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Elmisery, F. A., H. F. Hammed, A. E. Salama, and F. El-Geldawi. "Speaker identification system based on FPGA." In 2005 12th IEEE International Conference on Electronics, Circuits and Systems (ICECS 2005). IEEE, 2005. http://dx.doi.org/10.1109/icecs.2005.4633573.

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Costantini, Giovanni, Valerio Cesarini, and Fabio Paolizzo. "NMF Based System for Speaker Identification." In 2021 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT). IEEE, 2021. http://dx.doi.org/10.1109/metroind4.0iot51437.2021.9488491.

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Leu, Fang-Yie, and Guan-Liang Lin. "An MFCC-Based Speaker Identification System." In 2017 IEEE 31st International Conference on Advanced Information Networking and Applications (AINA). IEEE, 2017. http://dx.doi.org/10.1109/aina.2017.130.

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Alam, Md Shariful, and Muhammad S. A. Zilany. "Speaker Identification System Under Noisy Conditions." In 2019 5th International Conference on Advances in Electrical Engineering (ICAEE). IEEE, 2019. http://dx.doi.org/10.1109/icaee48663.2019.8975420.

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Nehra, Neelam, Pardeep Sangwan, and Divya Kumar. "Speaker Identification System Using CNN Approach." In 2021 International Conference on Industrial Electronics Research and Applications (ICIERA). IEEE, 2021. http://dx.doi.org/10.1109/iciera53202.2021.9726767.

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Tang, Jinjie. "Deep learning based speaker identification system." In DEAI 2024: 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence. ACM, 2024. http://dx.doi.org/10.1145/3675417.3675542.

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Byun, Sung-Woo, and Seok-Pil Lee. "Implementation of Speaker Identification Using Speaker Localization for Conference System." In The 2nd World Congress on Electrical Engineering and Computer Systems and Science. Avestia Publishing, 2016. http://dx.doi.org/10.11159/mhci16.110.

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Islam, Md Rashedul, Md Shafiul Azam, and Saleh Ahmed. "Speaker identification system using PCA & eigenface." In 2009 12th International Conference on Computer and Information Technology (ICCIT). IEEE, 2009. http://dx.doi.org/10.1109/iccit.2009.5407129.

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Reports on the topic "Speaker identification system"

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Jin, Qin, and Yun Wang. Integrated Robust Open-Set Speaker Identification System (IROSIS). Defense Technical Information Center, 2012. http://dx.doi.org/10.21236/ada562148.

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Mizrach, Amos, Michal Mazor, Amots Hetzroni, et al. Male Song as a Tool for Trapping Female Medflies. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7586535.bard.

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This interdisciplinaray work combines expertise in engineering and entomology in Israel and the US, to develop an acoustic trap for mate-seeking female medflies. Medflies are among the world's most economically harmful pests, and monitoring and control efforts cost about $800 million each year in Israel and the US. Efficient traps are vitally important tools for medfly quarantine and pest management activities; they are needed for early detection, for predicting dispersal patterns and for estimating medfly abundance within infested regions. Early detection facilitates rapid response to invasio
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