A robust approach to authorship verification using siamese deep learning: application in phishing email detection

Q1 Arts and Humanities

International Journal of Speech Technology Pub Date : 2024-06-14 DOI:10.1007/s10772-024-10110-y

Mohamed Abdelkarim Remmide, Fatima Boumahdi, Imane Rebeh Ammar Aouchiche, Amina Guendouz, Narhimene Boustia

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利用连体深度学习验证作者身份的稳健方法：在网络钓鱼电子邮件检测中的应用

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来源期刊

International Journal of Speech Technology ENGINEERING, ELECTRICAL & ELECTRONIC-

CiteScore

5.00

自引率

0.00%

发文量

期刊介绍： The International Journal of Speech Technology is a research journal that focuses on speech technology and its applications. It promotes research and description on all aspects of speech input and output, including theory, experiment, testing, base technology, applications. The journal is an international forum for the dissemination of research related to the applications of speech technology as well as to the technology itself as it relates to real-world applications. Articles describing original work in all aspects of speech technology are included. Sample topics include but are not limited to the following: applications employing digitized speech, synthesized speech or automatic speech recognition technological issues of speech input or output human factors, intelligent interfaces, robust applications integration of aspects of artificial intelligence and natural language processing international and local language implementations of speech synthesis and recognition development of new algorithms interface description techniques, tools and languages testing of intelligibility, naturalness and accuracy computational issues in speech technology software development tools speech-enabled robotics speech technology as a diagnostic tool for treating language disorders voice technology for managing serious laryngeal disabilities the use of speech in multimedia This is the only journal which presents papers on both the base technology and theory as well as all varieties of applications. It encompasses all aspects of the three major technologies: text-to-speech synthesis, automatic speech recognition and stored (digitized) speech.