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Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032912642 ISBN 13: 9781032912646
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Añadir al carritoPaperback. Condición: new. Paperback. Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Primarily used for person authentication, these systems strive to verify the speaker's claimed identity. Despite substantial technological advancements, recent testing has revealed persistent vulnerabilities to spoofing, commonly referred to as a spoof attack. Various techniques such as mimicry, replay, text to speech (TTS), and voice conversion (VC) are frequently employed in ASV systems to execute logical access (LA) or physical access (PA) spoofing attacks. To secure an ASD system from these attacks many researchers have proposed effective security models as countermeasures. In addition, numerous review papers by different researchers have discussed various countermeasures developed to secure ASD systems. However, there is a notable absence of an authored book that comprehensively addresses this critical research topic, encompassing frontend, backend, dataset and types of attacks considerations. Therefore, there is an urgent need for a book that serves as a valuable resource for upcoming researchers, offering insights into securing ASD systems and bridging the existing gap in the literature. Hence, this book is an effort by the authors in such direction. Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
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Añadir al carritoCondición: New. Mohit Dua earned his Ph.D. in Automatic Speech Recognition from the National Institute of Technology, Kurukshetra, India, in 2018. He is presently working as an assistant professor in the Department of Computer Engineering at NIT Kurukshetra, Indi.
Idioma: Inglés
Publicado por Taylor & Francis Ltd Mai 2026, 2026
ISBN 10: 1032912642 ISBN 13: 9781032912646
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 65,00
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware - Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Primarily used for person authentication, these systems strive to verify the speaker's claimed identity. Despite substantial technological advancements, recent testing has revealed persistent vulnerabilities to spoofing, commonly referred to as a spoof attack. Various techniques such as mimicry, replay, text to speech (TTS), and voice conversion (VC) are frequently used in ASV systems to execute logical access (LA) or physical access (PA) spoofing attacks. To protect an ASD system from these attacks, many researchers have proposed effective security models as countermeasures. In addition, numerous review papers by different researchers have discussed various countermeasures developed to secure ASD systems. However, there is a notable absence of an authored book that comprehensively addresses this critical research topic, encompassing frontend, backend, dataset, and types of attacks considerations. Therefore, there is an urgent need for a book that can serve as a valuable resource for upcoming researchers, offering insights into securing ASD systems and bridging the existing gap in the literature. Hence, this book represents an effort by the authors in that direction.
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Añadir al carritoTaschenbuch. Condición: Neu. Audio Spoof Detection from Theory to Practical Application | Mohit Dua (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2026 | Taylor & Francis Ltd | EAN 9781032912646 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2026
ISBN 10: 1032912642 ISBN 13: 9781032912646
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Añadir al carritoPaperback. Condición: new. Paperback. Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Primarily used for person authentication, these systems strive to verify the speaker's claimed identity. Despite substantial technological advancements, recent testing has revealed persistent vulnerabilities to spoofing, commonly referred to as a spoof attack. Various techniques such as mimicry, replay, text to speech (TTS), and voice conversion (VC) are frequently employed in ASV systems to execute logical access (LA) or physical access (PA) spoofing attacks. To secure an ASD system from these attacks many researchers have proposed effective security models as countermeasures. In addition, numerous review papers by different researchers have discussed various countermeasures developed to secure ASD systems. However, there is a notable absence of an authored book that comprehensively addresses this critical research topic, encompassing frontend, backend, dataset and types of attacks considerations. Therefore, there is an urgent need for a book that serves as a valuable resource for upcoming researchers, offering insights into securing ASD systems and bridging the existing gap in the literature. Hence, this book is an effort by the authors in such direction. Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days.
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Añadir al carritoCondición: New. Mohit Dua earned his Ph.D. in Automatic Speech Recognition from the National Institute of Technology, Kurukshetra, India, in 2018. He is presently working as an assistant professor in the Department of Computer Engineering at NIT Kurukshetra, Indi.
Idioma: Inglés
Publicado por Taylor & Francis Ltd Mai 2026, 2026
ISBN 10: 1032910534 ISBN 13: 9781032910536
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 164,23
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Añadir al carritoBuch. Condición: Neu. Neuware - Audio Spoof Detection (ASD) systems play a pivotal role in evaluating whether the input speech signal has been manipulated by an imposter attempting unauthorized access to an authentic user's account or if it genuinely originates from the declared user. Primarily used for person authentication, these systems strive to verify the speaker's claimed identity. Despite substantial technological advancements, recent testing has revealed persistent vulnerabilities to spoofing, commonly referred to as a spoof attack. Various techniques such as mimicry, replay, text to speech (TTS), and voice conversion (VC) are frequently used in ASV systems to execute logical access (LA) or physical access (PA) spoofing attacks. To protect an ASD system from these attacks, many researchers have proposed effective security models as countermeasures. In addition, numerous review papers by different researchers have discussed various countermeasures developed to secure ASD systems. However, there is a notable absence of an authored book that comprehensively addresses this critical research topic, encompassing frontend, backend, dataset, and types of attacks considerations. Therefore, there is an urgent need for a book that can serve as a valuable resource for upcoming researchers, offering insights into securing ASD systems and bridging the existing gap in the literature. Hence, this book represents an effort by the authors in that direction.
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