Dissertations / Theses on the topic 'Voice recognition'
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Kamarauskas, Juozas. "Speaker recognition by voice." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2009~D_20090615_093847-20773.
Full textDisertacijoje nagrinėjami kalbančiojo atpažinimo pagal balsą klausimai. Aptartos kalbančiojo atpažinimo sistemos, jų raida, atpažinimo problemos, požymių sistemos įvairovė bei kalbančiojo modeliavimo ir požymių palyginimo metodai, naudojami nuo ištarto teksto nepriklausomame bei priklausomame kalbančiojo atpažinime. Darbo metu sukurta nuo ištarto teksto nepriklausanti kalbančiojo atpažinimo sistema. Kalbėtojų modelių kūrimui ir požymių palyginimui buvo panaudoti Gauso mišinių modeliai. Pasiūlytas automatinis vokalizuotų garsų išrinkimo (segmentavimo) metodas. Šis metodas yra greitai veikiantis ir nereikalaujantis iš vartotojo jokių papildomų veiksmų, tokių kaip kalbos signalo ir triukšmo pavyzdžių nurodymas. Pasiūlyta požymių vektorių sistema, susidedanti iš žadinimo signalo bei balso trakto parametrų. Kaip žadinimo signalo parametras, panaudotas žadinimo signalo pagrindinis dažnis, kaip balso trakto parametrai, panaudotos keturios formantės bei trys antiformantės. Siekiant suvienodinti žemesnių bei aukštesnių formančių ir antiformančių dispersijas, jas pasiūlėme skaičiuoti melų skalėje. Rezultatų palyginimui sistemoje buvo realizuoti standartiniai požymiai, naudojami kalbos bei asmens atpažinime – melų skalės kepstro koeficientai (MSKK). Atlikti kalbančiojo atpažinimo eksperimentai parodė, kad panaudojus pasiūlytą požymių sistemą buvo gauti geresni atpažinimo rezultatai, nei panaudojus standartinius požymius (MSKK). Gautas lygių klaidų lygis, panaudojant pasiūlytą požymių... [toliau žr. visą tekstą]
Al-Kilani, Menia. "Voice-signature-based Speaker Recognition." University of the Western Cape, 2017. http://hdl.handle.net/11394/5888.
Full textPersonal identification and the protection of data are important issues because of the ubiquitousness of computing and these have thus become interesting areas of research in the field of computer science. Previously people have used a variety of ways to identify an individual and protect themselves, their property and their information. This they did mostly by means of locks, passwords, smartcards and biometrics. Verifying individuals by using their physical or behavioural features is more secure than using other data such as passwords or smartcards, because everyone has unique features which distinguish him or her from others. Furthermore the biometrics of a person are difficult to imitate or steal. Biometric technologies represent a significant component of a comprehensive digital identity solution and play an important role in security. The technologies that support identification and authentication of individuals is based on either their physiological or their behavioural characteristics. Live-‐data, in this instance the human voice, is the topic of this research. The aim is to recognize a person’s voice and to identify the user by verifying that his/her voice is the same as a record of his / her voice-‐signature in a systems database. To address the main research question: “What is the best way to identify a person by his / her voice signature?”, design science research, was employed. This methodology is used to develop an artefact for solving a problem. Initially a pilot study was conducted using visual representation of voice signatures, to check if it is possible to identify speakers without using feature extraction or matching methods. Subsequently, experiments were conducted with 6300 data sets derived from Texas Instruments and the Massachusetts Institute of Technology audio database. Two methods of feature extraction and classification were considered—mel frequency cepstrum coefficient and linear prediction cepstral coefficient feature extraction—and for classification, the Support Vector Machines method was used. The three methods were compared in terms of their effectiveness and it was found that the system using the mel frequency cepstrum coefficient, for feature extraction, gave the marginally better results for speaker recognition.
Alkilani, Menia Mohamed. "Voice signature based Speaker Recognition." University of the Western Cape, 2017. http://hdl.handle.net/11394/6196.
Full textPersonal identification and the protection of data are important issues because of the ubiquitousness of computing and these havethus become interesting areas of research in the field of computer science. Previously people have used a variety of ways to identify an individual and protect themselves, their property and their information.
Laird, Esther. "Voice recognition and auditory-visual integration in person recognition." Thesis, University of Sussex, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487906.
Full textClotworthy, Christopher John. "A study of automated voice recognition." Thesis, Queen's University Belfast, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.356909.
Full textDamjanovic, Ljubica. "Memory processes in familiar voice recognition." Thesis, University of Essex, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.413126.
Full textVipperla, Ravichander. "Automatic Speech Recognition for ageing voices." Thesis, University of Edinburgh, 2011. http://hdl.handle.net/1842/5725.
Full textIliadi, Konstantina. "Bio-inspired voice recognition for speaker identification." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/413949/.
Full textSanders, Richard Calvin. "Voice recognition system implementation and laboratory exercise." Master's thesis, This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-01262010-020212/.
Full textHo, Ching-Hsiang. "Speaker modelling for voice conversion." Thesis, Brunel University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365076.
Full textEriksson, Erik J. "That voice sounds familiar : factors in speaker recognition." Doctoral thesis, Umeå : Department of Philosophy and Linguistics, Umeå University, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1106.
Full textKuhn, Lisa Katharina. "Emotion recognition in the human face and voice." Thesis, Brunel University, 2015. http://bura.brunel.ac.uk/handle/2438/11216.
Full textM, Alzamora, Manuel I. Alzamora, Andrés E. Huamán, Alfredo Barrientos, and Riega Rosario del Pilar Villalta. "Implementación de una herramienta de integración de varios tipos de interacción humano-computadora para el desarrollo de nuevos sistemas multimodales." International Institute of Informatics and Systemics, IIIS, 2018. http://hdl.handle.net/10757/624676.
Full textRevisión por pares
Xue, Sukui, and 薛苏葵. "Voice-enabled CAD system." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2010. http://hub.hku.hk/bib/B45461405.
Full textPandit, Medha. "Voice and lip based speaker verification." Thesis, University of Surrey, 2000. http://epubs.surrey.ac.uk/915/.
Full textNayfeh, Taysir H. "Multi-signal processing for voice recognition in noisy environments." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-10222009-125021/.
Full textMalyska, Nicolas 1977. "Automatic voice disorder recognition using acoustic amplitude modulation features." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/30092.
Full textIncludes bibliographical references (p. 114-117).
An automatic dysphonia recognition system is designed that exploits amplitude modulations (AM) in voice using biologically-inspired models. This system recognizes general dysphonia and four subclasses: hyperfunction, A-P squeezing, paralysis, and vocal fold lesions. The models developed represent processing in the auditory system at the level of the cochlea, auditory nerve, and inferior colliculus. Recognition experiments using dysphonic sentence data obtained from the Kay Elemetrics Disordered Voice Database suggest that our system provides complementary information to state-of-the-art mel-cepstral features. A model for analyzing AM in dysphonic speech is also developed from a traditional communications engineering perspective. Through a case study of seven disordered voices, we show that different AM patterns occur in different frequency bands. This perspective challenges current dysphonia analysis methods that analyze AM in the time-domain signal.
by Nicolas Malyska.
S.M.
He, Qing Ph D. Massachusetts Institute of Technology. "An architecture for low-power voice-command recognition systems." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105574.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 149-157).
The advancements in fields such as machine-learning have allowed for a growing number of applications seeking to exploit learning methods. Many such applications involve complex algorithms working over high-dimensional features and are implemented in large scale systems where power and other resources are abundant. With emerging interest in embedded applications, nano-scale systems, and mobile devices, which are power and computation constrained, there is a rising need to find simple, low-power solutions for common applications such as voice activation. This thesis develops an ultra-low-power system architecture for voice-command recognition applications. It optimizes system resources by exploiting compact representations of the signal features and extracting them with efficient analog front-ends. The front-end performs feature pre-selection such that only a subset of all available features are chosen and extracted. Two variations of front-end feature extraction design are developed, for the applications of text-dependent speaker-verification and user-independent command recognition, respectively. For speaker-verification, the features are selected with knowledge of the speaker's fundamental frequency and are adapted based on the noise spectrum. The back-end algorithm, supporting adaptive feature selection, is a weighted dynamic time warping algorithm that removes signal misalignments and mitigates speech rate variations while preserving the signal envelope. In the case of user-independent command recognition, a universal set of features are selected without using speaker-specific information. The back-end classifier is enabled by a novel multi-band deep neural network model that processes only the selected features at each decision. In experiments, the proposed systems achieve improved accuracy with noise robustness using significantly less power consumption and computation than existing systems. Components of the front- and back-ends have been implemented in hardware, and the end-to-end system power consumption is kept under a few hundred [mu]Ws.
by Qing He.
Ph. D.
Lawy, Jenny. "Ethnography of San : minority recognition and voice in Botswana." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/22888.
Full textMathukumalli, Sravya. "Vocal combo android application." Kansas State University, 2016. http://hdl.handle.net/2097/32505.
Full textDepartment of Computing and Information Sciences
Mitchell L. Neilsen
Now-a-days people from various backgrounds need different information on demand. People are relying on web as a source of information they need. But to get connected to internet all the time with a computer system is not possible. Android, being open source has already made its mark in the mobile application development. The highest smart phone user base and the ease of developing the applications in Android is an added advantage for the users as well as the Android developers. The vocal combo is an Android application which provides the required functionality on Android supported smart phone or a tablet. This provides the flexibility of accessing information at the users’ fingertips. This application is built using Android SDK, which makes the application easy to deploy on any Android powered device. Vocal Combo is a combination of voice based applications. It includes a Text-To-Voice convertor and Voice-To-Text convertor. This application helps the user to learn the pronunciation of various words. At the same time the user can also check his/her pronunciation skills. This application also provides the functionality of meaning check where the user can check the meaning of the words he types in or speaks out. At any point of time, the user can check the history of the words for which he has checked the meaning or pronunciation for. The application also provides the support to the user on how to use this application.
Lingaria, Dhruvin M. "Assistive voice recognition device for GSM calling using Arduino UNO." Thesis, California State University, Long Beach, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1600584.
Full textDeveloping a smart home environment for the assistive living requires great efforts. The key element of the smart environment is the ubiquitous voice user interface with several additional capabilities such as the recognition of several gestures, which can be a new feature of voice controlled devices. There are many identification technologies used in current intelligent guard systems. Relative to other techniques, the voice recognition technology is generally regarded as one of the convenient and safe recognition techniques. The assistive device project has incorporated the technology of voice recognition to perform the GSM calling. Arduino UNO is the microprocessor used to create an interface between the voice module and the GSM module SIM900. Platform was developed using inexpensive hardware and software elements available on the market People with disabilities showed high robustness for assistive device. Sample voice commands were stored in the temporary memory for the ATMEGA 328P when field tests with several sets of voice commands was done. The GSM module SIM900 could easily connect to the local cellular network carriers. Hence voice recognized emergency calling can be the future of biomedical field.
Wilson, Shawn C. "Voice recognition systems : assessment of implementation aboard U.S. naval ships." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Mar%5FWilson.pdf.
Full textThesis advisor(s): Michael T. McMaster, Kenneth J. Hagan. Includes bibliographical references (p. 47-49). Also available online.
Pillay, Surosh Govindasamy. "Voice biometrics under mismatched noise conditions." Thesis, University of Hertfordshire, 2011. http://hdl.handle.net/2299/5531.
Full textWildermoth, 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.
Full textWildermoth, Brett Richard. "Text-Independent Speaker Recognition Using Source Based Features." Thesis, Griffith University, 2001. http://hdl.handle.net/10072/366289.
Full textThesis (Masters)
Master of Philosophy (MPhil)
School of Microelectronic Engineering
Faculty of Engineering and Information Technology
Full Text
Mangayyagari, Srikanth. "Voice recognition system based on intra-modal fusion and accent classification." [Tampa, Fla.] : University of South Florida, 2007. http://purl.fcla.edu/usf/dc/et/SFE0002229.
Full textRashid, M. A. "Packet voice communication on carrier sense multiple access local area networks." Thesis, University of Strathclyde, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.381531.
Full textGibson, Marcia Rose. "A feasibility study on the use of a voice recognition system for training delivery." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-08252008-162853/.
Full textRouse, Kenneth Arthur Gilbert Juan E. "Classifying speakers using voice biometrics In a multimodal world." Auburn, Ala, 2009. http://hdl.handle.net/10415/1824.
Full textSepasian, Mojtaba. "Multibiometric security in wireless communication systems." Thesis, Brunel University, 2010. http://bura.brunel.ac.uk/handle/2438/5081.
Full textD'Silva, Reginald Arthur. "Promoting reading skills of young adult EAL learners through voice recognition software." Thesis, University of British Columbia, 2011. http://hdl.handle.net/2429/37665.
Full textMACIÁ, ABEL SEBASTIÁN SANTAMARINA. "AN EVALUATION OF BIMODAL RECOGNITION SYSTEMS BASED ON VOICE AND FACIAL IMAGES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=29315@1.
Full textCOORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
PROGRAMA DE EXCELENCIA ACADEMICA
Esta dissertação tem como objetivo avaliar os métodos de fusão de escores mais importantes na combinação de dois sistemas uni-modais de reconhecimento em voz e imagens faciais. Para cada sistema uni-modal foram implementadas duas técnicas de classificação: o GMM/UBM e o I-Vetor/GPLDA para voz e o GMM/UBM e um classificador baseado em LBP para imagens faciais. Estes sistemas foram combinados entre eles, sendo 4 combinações testadas. Os métodos de fusão de escores escolhidos se dividem em três grupos: Fusão baseada em densidade, fusão baseada em transformação e fusão baseada em classificadores, e foram testadas algumas variantes para cada grupo. Os métodos foram avaliados em modo de verificação, usando duas bases de dados, uma base virtual formada por duas bases uni-modais e outra base bimodal. O resultado de cada técnica bimodal empregada foi comparado com os resultados das técnicas uni-modais, percebendo-se ganhos significativos na acurácia de reconhecimento. As técnicas de fusão baseadas em densidade mostraram os melhores resultados entre todas as outras técnicas, mais apresentaram uma maior complexidade computacional por causa do processo de estimação da densidade.
The main objective of this dissertation is to compare the most important approaches for score-level fusion of two unimodal systems consisting of facial and independent speaker recognition systems. Two classification methods for each biometric modality were implemented: a GMM/UBM and an I-Vector/GPLDA classifiers for speaker independent recognition and a GMM/UBM and LBP-based classifiers for facial recognition, resulting in four different multimodal combination of fusion explored. The score-level fusion methods investigated are divided in Density-based, Transformation-based and Classifier-based groups and few variants on each group are tested. The fusion methods were tested in verification mode, using two different databases, one virtual database and a bimodal database. The results of each bimodal fusion technique implemented were compared with the unimodal systems, which showed significant recognition performance gains. Density-based techniques of fusion presented the best results among all fusion approaches, at the expense of higher computational complexity due to the density estimation process.
Johnson, Joanna. "The effectiveness of voice recognition technology as used by persons with disabilities." Online version, 1998. http://www.uwstout.edu/lib/thesis/1998/1998johnsonj.pdf.
Full textCount, Peter. "Utilising voice recognition software to improve reading fluency of struggling adolescent readers." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2016. https://ro.ecu.edu.au/theses/1799.
Full textFredrickson, Steven Eric. "Neural networks for speaker identification." Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294364.
Full textHannah, Malcolm Ian. "Prospects for applying speaker verification to unattended secure banking." Thesis, University of Abertay Dundee, 1996. http://eprints.soton.ac.uk/256265/.
Full textHuliehel, Fakhralden A. "An RBFN-based system for speaker-independent speech recognition." Diss., This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-06062008-162619/.
Full textMELLO, SIMON. "VATS : Voice-Activated Targeting System." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279837.
Full textMaskininlärning är viktigt inom röstigenkänning och datorseende, för både små såväl som stora applikationer. Syftet med det här projektet är att titta på om enkla implementationer av maskininlärning duger för den verkligen världen. Ett enkelt artificiellt neuronnät kodat i Python, samt existerande programbibliotek för Python, används för att kontrollera en laserpekare via en servomotor och en Arduino, för att skapa ett röstaktiverat identifieringssystem. Neuronnätet tränat på MNIST data når en precision på 0.95 ± 0.01 när den försöker klassificera MNIST test data, men lyckas även klassificera inspelade bilder korrekt om störningen är låg. Detta gäller även för röstigenkänningen, då den sällan ger fel avläsningar. Den slutliga prototypen lyckas i alla domäner förutom att förvandla bilder som klassificerats korrekt till mål som Arduinon kan läsa av och sikta på, vilket betyder att prototypen inte lyckas sammanfoga röstigenkänningen och datorseendet.
DeVilliers, Edward Michael. "Implementing voice recognition and natural language processing in the NPSNET networked virtual environment." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA320340.
Full textThesis advisor(s): Nelson D. Ludlow, John S. Falby. "September 1996." Includes bibliographical references (p. 171-175). Also available online.
Bruijn, Christina Geertruida de. "Voice quality after dictation to speech recognition software : a perceptual and acoustic study." Thesis, University of Sheffield, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440907.
Full textCooper, R. E. "Own-group biases in face and voice recognition : perceptual and social-cognitive influences." Thesis, University of Essex, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.702477.
Full textGeoffroy, Nancy Anne. "Measuring Speech Intelligibility in Voice Alarm Communication Systems." Link to electronic thesis, 2005. http://www.wpi.edu/Pubs/ETD/Available/etd-050405-192800/.
Full textKeywords: speech intelligibility; voice alarm communication system; common intelligibility scale (CIS); speech transmission index (STI). Includes bibliographical references (p. 80-82).
Kisel, Andrej. "Person Identification by Fingerprints and Voice." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2010~D_20101230_093643-05320.
Full textPenkiose disertacijos darbo dalyse nagrinėjamos žmogaus identifikavimo pagal pirštų atspaudus ir balsą problemos ir siūlomi jų sprendimai. Pirštų atspaudų požymių išskyrimo algoritmų kokybės įvertinimo problemą siūloma spręsti panaudojant sintezuotus pirštų atspaudus. Darbe siūlomos žinomo pirštų atpaudų sintezės algoritmo modifikacijos, kurios leidžia sukurti piršto atspaudo vaizdą su iš anksto nustatytomis charakteristikomis ir požymiais bei pagreitina sintezės procesą. Pirštų atspaudų požymių palyginimo problemos yra aptartos ir naujas palyginimo algoritmas yra siūlomas deformuotų pirštų palyginimui. Algoritmo kokybė yra įvertinta ant viešai prieinamų ir vidinių duomenų bazių. Naujas asmens identifikavimo pagal balsą metodas remiantis tiesinės prognozės modelio grupinės delsos požymiais ir tų požymių palyginimo metrika kokybės prasme lenkia tradicinius asmens identifikavimo pagal balsą metodus. Pirštų ir balso įrašų nepriklausomumas yra irodytas ir asmens atpažinimas pagal balsą ir pirštų atspaudus kartu yra pasiūlytas siekiant išspręsti bendras biometrinių sistemų problemas.
Kay, Peter. "A speech input modality for computer-aided drawing : user interface issues." Thesis, University of Hertfordshire, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260794.
Full textЯкушев, Олександр Анатолійович, Александр Анатольевич Якушев, Oleksandr Anatoliiovych Yakushev, and О. В. Кєтов. "Інформаційне та програмне забезпечення мультисенсорної системи розпізнавання неправди." Thesis, Вид-во СумДУ, 2008. http://essuir.sumdu.edu.ua/handle/123456789/20856.
Full textHolmes, William Paul. "Voice input for the disabled /." Title page, contents and summary only, 1987. http://web4.library.adelaide.edu.au/theses/09ENS/09ensh749.pdf.
Full textTypescript. Includes a copy of a paper presented at TADSEM '85 --Australian Seminar on Devices for Expressive Communication and Environmental Control, co-authored by the author. Includes bibliographical references (leaves [115-121]).
Ali, Asif. "Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50363.
Full textBenavent, Chàfer José Vicente. "Voice line-ups: Testing aural-perceptual recognition on native speakers of a foreign language." Doctoral thesis, Universitat de Barcelona, 2020. http://hdl.handle.net/10803/668733.
Full textEl punto fundamental de esta tesis doctoral se centra en el reconocimiento y percepción de hablantes extranjeros/nativos. Para examinar dichos fenómenos, participantes de universidades británicas y españolas fueron seleccionados como jueces de las encuestas de percepción confeccionadas para este fin (ruedas de reconocimiento con tres tipos de lenguas diferenciadas: inglés, español y neerlandés), y así desentrañar las relaciones existentes entre el porcentaje de aciertos/errores en tareas de identificación y discriminación de locutores y los factores inherentes al hablante, como el perfil sociolingüístico y los parámetros acústicos pertinentes. Para ahondar nuestra comprensión de las circunstancias reales, los datos usados se ajustaron debidamente (duración reducida de grabaciones semi-espontáneas), lo que contrasta con las condiciones ideales y controladas hasta ahora empleadas en experimentos de este tipo. Desde un punto de vista metodológico, ésta es una de las principales contribuciones de la presente tesis, además de ser uno de sus retos, ya que pretende demostrar la viabilidad del análisis acústico en la discriminación de hablantes pese a las limitaciones dadas por el material analizado. Se concluye que la familiaridad del idioma no condicionó los resultados obtenidos. Aun así, las lenguas aprendidas exhibieron un comportamiento impredecible. Por otro lado, el análisis acústico produjo una tasa de errores inferior a las producidas por el jurado en pruebas deidentificación. Sin embargo, las tareas dediscriminación mostraron aún menos falsas alarmas en los participantes, con la excepción del análisis de muestras inglesas (con una tasa de error del 0%). En virtud de lo expuesto, se recomienda seguir con esta línea de investigación para verificar dichas afirmaciones. Por otro lado, las limitaciones radican en la interdisciplinariedad del reconocimiento de locutores y en la presencia de influencias coexistentes incontrolables como los estados psicológicos, la memoria y los factores medioambientales. Pese a la falta de contundencia de las pruebas estadísticas, esta tesis nos lleva un paso más cerca hacia la comprensión de las complejidades inherentes a la comparación forense de voces en casos reales mediante el análisis de habla semi-espontánea, cuya información es probablemente más difícil de analizar que la encontrada en grabaciones de laboratorio.
El punt fonamental d’aquesta tesi doctoral se centra en el reconeixement i percepció de parlants estrangers/nadius. Per a examinar aquests fenòmens, participants d’universitats britàniques i espanyoles es seleccionaren com a jutges de les enquestes de percepció confeccionades per a aquesta fi (rodes de reconeixement amb tres tipus de llengües diferenciades: anglès, espanyol i neerlandès), i així investigar les relacions existents entre el percentatge d’encerts/errors en tasques d’identificació i discriminació de locutors i els factors inherents al parlant, com el perfil sociolingüístic i els paràmetres acústics pertinents. Per a aprofundir la nostra comprensió de les circumstàncies reals, les dades emprades s’ajustaren degudament (durada reduïda de gravacions semi-espontànies), la qual cosa contrasta amb les condicions ideals i controlades que s’usaven fins ara en experiments d’aquest tipus. Des d’un punt de vista metodològic, aquesta és una de les contribucions principals de la present tesi, a més de ser un dels seus reptes, ja que pretén demostrar la viabilitat de l’anàlisi acústica en la discriminació de parlants malgrat les limitacions donades pel material analitzat. Es conclou que la familiaritat de l’idioma no ha condicionat els resultats obtinguts. Així i tot, les llengües apreses exhibiren un comportament impredictible. D’altra banda, l’anàlisi acústica causa una taxa d’error inferior a les produïdes pel jurat en proves d’identificació. No obstant això, les tasques de discriminació mostraren encara menys falses alarmes en els participants, amb l’excepció de l’anàlisi en mostres angleses (amb una taxa d’error del 0%). Tenint en compte l’anterior, es recomana seguir amb aquesta línia de recerca per poder verificar les afirmacions ja esmentades. Encara més, les limitacions radiquen en la interdisciplinarietat del reconeixement de locutors i en la presència d’influències coexistents incontrolables com els estats psicològics, la memòria i els factors mediambientals. Malgrat la insuficient contundència de les proves estadístiques, aquesta tesi ens porta un pas més prop cap a la comprensió de les complexitats inherents a la comparació forense de veus en casos reals mitjançant l’anàlisi de parla semi-espontània, la informació de la qual és probablement més difícil d’analitzar que el que s’enregistra a les mostres de laboratori.
Jafari, Moghadamfard Ramtin, and Saeid Payvar. "The Potential of Visual Features : to Improve Voice Recognition Systems in Vehicles Noisy Environment." Thesis, Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-27273.
Full textCouroux, Christina. "Neighbor-stranger discrimination and individual recognition by voice in the American redstart (Setophaga ruticilla)." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape16/PQDD_0027/MQ37111.pdf.
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