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Journal articles on the topic 'Artificial Intelligence Generated Speech (AIGS)'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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1

Faiz, Ullah. "A Phonetic Forensic Analysis of Imran Khan's Speeches." Kurdish Studies 12, no. 4 (2024): 720–32. https://doi.org/10.5281/zenodo.11420889.

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The objective of this research was to analyze the speeches made by Al Tools and Imran Khan. Praat played a crucial role in conducting this analysis. Nowadays, there are numerous fake videos and audios associated with specific individuals. For instance, speeches made by Al Tools, such as Imran Khan's speech after being imprisoned, were released. The researcher obtained these videos from online sources and compared them. The first video focused on Israel's attack on Gaza, which was a speech generated by artificial intelligence (AIGS), while the second speech addressed th

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Wei, Wenlu, and Zhichao Song. "AIGC Generative Speech Technology: An Examination of Its Communication Paradigms and Evolutionary Reflections." Philosophy and Social Science 1, no. 5 (2024): 41–46. http://dx.doi.org/10.62381/p243507.

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The emergence of Artificial Intelligence Generated Content (AIGC) represents a new opportunity for the development of intelligent communication. The development of AIGC technology has given rise to new media transformations, creating new content production and dissemination methods. As one of the core areas of the AIGC application, generative speech technology, due to its low cost and simplicity, has been widely used in scenarios such as audiovisual narration, artificial intelligence anchor broadcasting, and audiobook content production. However, the use of AIGC-generated content in practice,

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Li, Mengxi. "Interpreting Classroom Teaching for Translation Majors in the AIGC Era." World Journal of Educational Research 11, no. 4 (2024): p11. http://dx.doi.org/10.22158/wjer.v11n4p11.

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The rapid development of Artificial Intelligence Generated Content represented by ChatGPT has triggered a new round of artificial intelligence revolution, and has also brought unprecedented changes to the field of education. As far as translation majors are concerned, although all major universities have opened interpreting majors or interpreting courses and shouldered the responsibility of training interpreting talents for society, due to the influence of teaching staff, student quality and teaching mode, English majors in colleges and universities have encountered great challenges in trainin

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Kallamadugu, Althaf Hussain, Nurudeen Segun Lawal, and Joseph Michael Burgett. "A Workflow for Creating Narration for Voice-Over Presentation Using Commercially Available Artificial Intelligence." Journal of Advanced Technological Education (J ATE) 3, no. 2 (2024): 152–57. https://doi.org/10.5281/zenodo.13989064.

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This rapid communication presents a multi-step workflow for recreating existing course lectures using artificial intelligence (AI) and natural language processing (NLP). The workflow encompasses audio extraction from original lectures, transcript refinement via ChatGPT and human proofreading, audio regeneration through text-to-speech, closed captioning, presentation recreation with AI-generated content, and the development of supplementary resources like study guides and AI chatbots. The implemented approach leverages AI to enhance educational accessibility and personalization while balancing

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Tan, Saw Fen. "Perceptions of students on artificial intelligence-generated content avatar utilization in learning management system." Asian Association of Open Universities Journal 19, no. 2 (2024): 170–85. http://dx.doi.org/10.1108/aaouj-12-2023-0142.

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PurposeThis study aims to explore students’ perceptions of the use of an artificial intelligence-generated content avatar (AIGC avatar) within a learning management system (LMS).Design/methodology/approachThis qualitative research involved seven postgraduate students. Data were collected through individual, in-depth interviews. The videos of the AIGC avatar, created using Leonardo, ChatGPT and Heygen, were uploaded to the LMS to communicate with students for the purposes of a welcome note, assignment guide, assignment feedback, tutorial reminders and preparation as well as to provide encourage

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Song, Yanying, and Wei Xiong. "Large Language Model-Driven 3D Hyper-Realistic Interactive Intelligent Digital Human System." Sensors 25, no. 6 (2025): 1855. https://doi.org/10.3390/s25061855.

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Digital technologies are undergoing comprehensive integration across diverse domains and processes of the human economy, politics, culture, society, and ecological civilization. This integration brings forth novel concepts, formats, and models. In the context of the accelerated convergence between the digital and physical worlds, a discreet yet momentous transformation is being steered by artificial intelligence generated content (AIGC). This transformative force quietly reshapes and potentially disrupts the established patterns of digital content production and consumption. Consequently, it h

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S, Kovalevskyy, Kovalevska O, and Sidyuk D. "Resonance diagnostics of production space of generative systems of artificial intelligence." Artificial Intelligence 28, AI.2023.28(2)) (2023): 94–106. http://dx.doi.org/10.15407/jai2023.02.094.

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The development of artificial intelligence generative systems (AIGS) in the modern world requires addressing issues related to the quality, stability, and efficiency of the generated content. In this context, resonance diagnostics become of paramount importance. The purpose of this study is to explore the possibilities of applying resonance diagnostics for detecting, analyzing, and resolving problems in artificial intelligence generative systems. To achieve the set goal, the following tasks were identified: analysis of the theoretical foundations of resonance diagnostics; investigation of the

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8

Balling, Laura Winther, Lasse Lohilahti Mølgaard, Oliver Townend, and Jens Brehm Bagger Nielsen. "The Collaboration between Hearing Aid Users and Artificial Intelligence to Optimize Sound." Seminars in Hearing 42, no. 03 (2021): 282–94. http://dx.doi.org/10.1055/s-0041-1735135.

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AbstractHearing aid gain and signal processing are based on assumptions about the average user in the average listening environment, but problems may arise when the individual hearing aid user differs from these assumptions in general or specific ways. This article describes how an artificial intelligence (AI) mechanism that operates continuously on input from the user may alleviate such problems by using a type of machine learning known as Bayesian optimization. The basic AI mechanism is described, and studies showing its effects both in the laboratory and in the field are summarized. A cruci

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Jyoshna, Girika, and Md Zia Ur Rahman. "An Intelligent reference free adaptive learning algorithm for speech enhancement." Journal of Intelligent & Fuzzy Systems 42, no. 3 (2022): 1895–906. http://dx.doi.org/10.3233/jifs-211249.

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Removing of noise component is an important task in all practical applications like hearing aids, speech therapy etc. In speech communication applications the speech components are contaminated with various types of noises. Separation of speech and noise component is a key issue in hearing aids, speech therapy applications. This paper demonstrates a hybrid version of singular spectrum analysis (SSA) and independent component analysis (ICA) based adaptive noise canceller (ANC) to separate noise and speech components. As ICA is not suitable for single channel sources, SSA is used to map signal c

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Evi Chamalah, Aida Azizah, Yosi Wulandari, and Oktarina Puspita Wardani. "Artificial intelligence media-assisted storytelling therapy as a solution for handling speech delay in early childhood." BAHASTRA 45, no. 1 (2025): 166–74. https://doi.org/10.26555/bs.v45i1.1245.

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This study investigates the effectiveness of Gemini AI-assisted storytelling therapy as an innovative approach to addressing speech delays in early childhood. Through qualitative methodology incorporating case studies, literature review, and action research with children aged 6-8 years, participants engaged in therapeutic storytelling sessions facilitated by Gemini AI, which generated personalized narratives based on individual abilities while providing real-time analysis of verbal responses. The AI system's adaptive algorithms continuously refined story content to match each child's developme

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Gyéresi, Júlia. "Az MI által generált beszéd jellemzői." Symbolon 25, no. 2 (47) (2024): 83–87. http://dx.doi.org/10.46522/s.2024.02.6.

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Success in life is not primarily attributed to cognitive skills. Rather, it is the level of development in social skills that creates real connections, forms relationships, and keeps attention engaged. There are a few human abilities that, for the time being, can still compete with artificial intelligence: our capacity for critical thinking, and our intelligence for dealing with human emotions and relationships. Machines are better at active attention, as they are able to pay attention continuously, without interruption. In our attention-deficient society, this is a fact of prime importance. S

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Norval, Michael, and Zenghui Wang. "Explainable Artificial Intelligence Techniques for Speech Emotion Recognition: A Focus on XAI Models." Inteligencia Artificial 28, no. 76 (2025): 85–123. https://doi.org/10.4114/intartif.vol28iss76pp85-123.

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This study employs Explainable Artificial Intelligence (XAI) techniques, including SHAP, LIME, and XGBoost, to interpret speech-emotion recognition (SER) models. Unlike previous work focusing on generic datasets, this research integrates these tools to explore the unique emotional nuances within an Afrikaans speech corpus. The complexity of architectures poses significant challenges regarding model interpretability. This paper explicitly aims to bridge the gaps in existing Speech Emotion Recognition (SER) systems by integrating advanced Explainable Artificial Intelligence (XAI) techniques. The

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Utkarsh, Verma, and Padmanaban R. Dr. "Speech Cloning: Text-To-Speech Using VITS." Engineering and Technology Journal 9, no. 05 (2024): 3951–56. https://doi.org/10.5281/zenodo.11158985.

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Voice is one of the most common and natural communication methods for humans. Voice is becoming the primary interface for AI voice assistants like Amazon Alexa, as well as in autos and smart home devices. Homes and so on. As human-machine communication becomes more common, researchers are exploring technology that mimics genuine speech. Speech cloning is the practice of copying or mimicking another person's speech, usually utilizing modern technology and artificial intelligence (AI). This entails producing a synthetic or cloned version of someone's voice that sounds very similar to the actual

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Mai, Kimberly T., Sergi Bray, Toby Davies, and Lewis D. Griffin. "Warning: Humans cannot reliably detect speech deepfakes." PLOS ONE 18, no. 8 (2023): e0285333. http://dx.doi.org/10.1371/journal.pone.0285333.

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Speech deepfakes are artificial voices generated by machine learning models. Previous literature has highlighted deepfakes as one of the biggest security threats arising from progress in artificial intelligence due to their potential for misuse. However, studies investigating human detection capabilities are limited. We presented genuine and deepfake audio to n = 529 individuals and asked them to identify the deepfakes. We ran our experiments in English and Mandarin to understand if language affects detection performance and decision-making rationale. We found that detection capability is unre

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Wang, Faye F. "Copyright Protection for AI-Generated Works." Amicus Curiae 5, no. 1 (2023): 88–103. http://dx.doi.org/10.14296/ac.v5i1.5663.

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Since the 2010s, artificial intelligence (AI) has quickly grown from another subset of machine learning (ie deep learning) in particular with recent advances in generative AI, such as ChatGPT. The use of generative AI has gone beyond leisure purposes. It has now been widely used to generate music, news articles and image-based art works. This prompts a regulatory interpretation as to how AI-generated works should be appropriately used to eliminate their potential harm to society, but at the same time how it should be protected to foster human creativity and promote a well-functioning market. T

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Cherkasova, Marina Nikolaevna, та Anna Valer’evna Taktarova. "Artificially generated academic text (а linguopragmatic aspect)". Philology. Issues of Theory and Practice 17, № 7 (2024): 2551–57. http://dx.doi.org/10.30853/phil20240363.

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In the process of integrating ‘artificial intelligence’ (AI) technologies into academic discourse, the procedure of writing an academic text is changing, and a new type of communicative interaction is formed – AI as the author of a ‘generated text’ (GТ) and a human being as the recipient of a text from AI. The aim of the study is to substantiate the perception of such a text by the recipient from the point of view of pragmalinguistic analysis on the basis of the identified features and indicators. An analysis of the functioning of artificially generated academic text is presented (5 scientific

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Guo, Juan. "Innovative Application of Sensor Combined with Speech Recognition Technology in College English Education in the Context of Artificial Intelligence." Journal of Sensors 2023 (February 11, 2023): 1–11. http://dx.doi.org/10.1155/2023/9281914.

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English listening is an effective way to improve students’ English expression ability and use oral communication. However, from the current situation of English teaching, the current English teaching methods are too single, and teachers do not focus on oral training in the classroom, resulting in low efficiency of classroom teaching. On the basis of following the principles of wholeness, interaction, balance, and sustainable development of educational ecology, by enhancing the synergy of ecological elements of English speaking classroom, promoting interactive dialogue among ecological subjects

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Kankevičiūtė, Eglė, Milita Songailaitė, Bohdan Zhyhun, and Justina Mandravickaitė. "LITHUANIAN HATE SPEECH CLASSIFICATION USING DEEP LEARNING METHODS." Automation of technological and business processes 15, no. 3 (2023): 20–29. http://dx.doi.org/10.15673/atbp.v15i3.2621.

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The ever-increasing amount of online content and the opportunity for everyone to express their opinions online leads to frequent encounters with social problems: bullying, insults, and hate speech. Some online portals are taking steps to stop this, such as no longer allowing user-generated comments to be made anonymously, removing the possibility to comment under the articles, and some portals employ moderators who identify and eliminate hate speech. However, given the large number of comments, an appropriately large number of people are required to do this work. The rapid development of artif

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Helzerman, R. A., and M. P. Harper. "MUSE CSP: An Extension to the Constraint Satisfaction Problem." Journal of Artificial Intelligence Research 5 (November 1, 1996): 239–88. http://dx.doi.org/10.1613/jair.298.

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This paper describes an extension to the constraint satisfaction problem (CSP) called MUSE CSP (MUltiply SEgmented Constraint Satisfaction Problem). This extension is especially useful for those problems which segment into multiple sets of partially shared variables. Such problems arise naturally in signal processing applications including computer vision, speech processing, and handwriting recognition. For these applications, it is often difficult to segment the data in only one way given the low-level information utilized by the segmentation algorithms. MUSE CSP can be used to compactly repr

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Velasco-Álvarez, Francisco, Álvaro Fernández-Rodríguez, and Ricardo Ron-Angevin. "Brain-computer interface (BCI)-generated speech to control domotic devices." Neurocomputing 509 (October 2022): 121–36. http://dx.doi.org/10.1016/j.neucom.2022.08.068.

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Chen, Caiyue. "Speech Synthesis Technology: Status and Challenges." ITM Web of Conferences 73 (2025): 02006. https://doi.org/10.1051/itmconf/20257302006.

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In recent years, speech synthesis technology has been more widely used in the field of artificial intelligence and human-computer interaction due to the excess of machine learning models to deep learning models. With the rise and development of applications such as intelligent voice assistants, voice navigation systems, generative macro modelling, and virtual reality, Users’ demand for voice systems is not limited to the generated sound as cold as robots and full of “inhuman” tones and rhythm, it is also desired to generate speech that is more natural, fluent, and free of mechanical sensations

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22

Williams, Emily L., Karl O. Jones, Colin Robinson, Sebastian Chandler Crnigoj, Helen Burrell, and Suzzanne McColl. "How Frequency and Harmonic Profiling of a ‘Voice’ Can Inform Authentication of Deepfake Audio: An Efficiency Investigation." Journal of Advances in Engineering and Technology 3, no. 1 (2025): 49–58. https://doi.org/10.54389/hgbc7543.

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As life in the digital era becomes more complex, the capacity for criminal activity within the digital realm becomes even more widespread. More recently, the development of deepfake media generation powered by Artificial Intelligence pushes audio and video content into a realm of doubt, misinformation, or misrepresentation. The instances of deepfake videos are numerous, with some infamous cases ranging from manufactured graphic images of the musician Taylor Swift, through to the loss of $25 million dollars transferred after a faked video call. The problems of deepfake are becoming increasingly

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Doppa, J. R., A. Fern, and P. Tadepalli. "HC-Search: A Learning Framework for Search-based Structured Prediction." Journal of Artificial Intelligence Research 50 (June 19, 2014): 369–407. http://dx.doi.org/10.1613/jair.4212.

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Structured prediction is the problem of learning a function that maps structured inputs to structured outputs. Prototypical examples of structured prediction include part-of-speech tagging and semantic segmentation of images. Inspired by the recent successes of search-based structured prediction, we introduce a new framework for structured prediction called HC-Search. Given a structured input, the framework uses a search procedure guided by a learned heuristic H to uncover high quality candidate outputs and then employs a separate learned cost function C to select a final prediction among thos

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Wagh, Ms Pranali, Sahil Desai, Purav Doshi, Chaitanya Gajoor, and Advait Narkar. "AI Generated Cricket Score using NLP." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42922.

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To create an AI-based system for creating real- time cricket scorecards using live or recorded commentary, this study investigates the integration of Natural Language Processing (NLP), audio recognition, and machine learning approaches. Along with team names and venue information, users can stream live commentary using a microphone or upload audio files using the system’s user-friendly frontend, Streamlit. Speech recognition is used to process and turn the audio into text, which is subsequently tokenized and subjected to NLP techniques to extract important events like runs, wickets, and overs.

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Lee, Jai-Hua, Pei-Song Chee, Eng-Hock Lim, and Chun-Hui Tan. "Artificial Intelligence-Assisted Throat Sensor Using Ionic Polymer–Metal Composite (IPMC) Material." Polymers 13, no. 18 (2021): 3041. http://dx.doi.org/10.3390/polym13183041.

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Throat sensing has received increasing demands in recent years, especially for oropharyngeal treatment applications. The conventional videofluoroscopy (VFS) approach is limited by either exposing the patient to radiation or incurring expensive costs on sophisticated equipment as well as well-trained speech-language pathologists. Here, we propose a smart and non-invasive throat sensor that can be fabricated using an ionic polymer–metal composite (IPMC) material. Through the cation’s movement inside the IPMC material, the sensor can detect muscle movement at the throat using a self-generated sig

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Pinska-Chauvin, Ella, Hartmut Helmke, Jelena Dokic, Petri Hartikainen, Oliver Ohneiser, and Raquel García Lasheras. "Ensuring Safety for Artificial-Intelligence-Based Automatic Speech Recognition in Air Traffic Control Environment." Aerospace 10, no. 11 (2023): 941. http://dx.doi.org/10.3390/aerospace10110941.

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This paper describes the safety assessment conducted in SESAR2020 project PJ.10-W2-96 ASR on automatic speech recognition (ASR) technology implemented for air traffic control (ATC) centers. ASR already now enables the automatic recognition of aircraft callsigns and various ATC commands including command types based on controller–pilot voice communications for presentation at the controller working position. The presented safety assessment process consists of defining design requirements for ASR technology application in normal, abnormal, and degraded modes of ATC operations. A total of eight f

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Genç, A. C., F. Turkoglu Genc, Z. N. Kaya, and E. Gönüllü. "AB1701 HOW TO MAKE A VIRTUAL PRESENTATION USING ARTIFICIAL INTELLIGENCE?" Annals of the Rheumatic Diseases 82, Suppl 1 (2023): 2088.2–2089. http://dx.doi.org/10.1136/annrheumdis-2023-eular.6257.

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BackgroundVirtual presentations have become increasingly common due to the COVID-19 pandemic and advancements in technology. However, it is not yet clear how to effectively use artificial intelligence (AI) in virtual presentations to enhance their effectiveness.ObjectivesThe aim of this study is to investigate the current state of AI in virtual presentations and to develop practical guidelines for using AI to enhance the effectiveness of virtual presentations.MethodsChatGPT is an artificial intelligence chatbot [1]. The final version contains information up to years of 2021. We wrote to ChatGP

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Tan, Choon Beng, Mohd Hanafi Ahmad Hijazi, Frazier Kok, Mohd Saberi Mohamad, and Puteri Nor Ellyza Nohuddin. "Artificial speech detection using image-based features and random forest classifier." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 1 (2022): 161. http://dx.doi.org/10.11591/ijai.v11.i1.pp161-172.

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The ASVspoof 2015 Challenge was one of the efforts of the research community in the field of speech processing to foster the development of generalized countermeasures against spoofing attacks. However, most countermeasures submitted to the ASVspoof 2015 Challenge failed to detect the S10 attack effectively, the only attack that was generated using the waveform concatenation approach. Hence, more informative features are needed to detect previously unseen spoofing attacks. This paper presents an approach that uses data transformation techniques to engineer image-based features together with ra

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Venkatesan, K. G. S., Alugonda Rajani, and Ramesh Kumar Yadav. "Automated Hate Speech Classification through Emotion Analysis in Social Media User-Generated Texts." International Journal of Scientific Methods in Intelligence Engineering Networks 01, no. 09 (2023): 27–34. http://dx.doi.org/10.58599/ijsmien.2023.1904.

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The incidence of online hate speech has experienced a significant increase in recent years, mostly ascribed to the widespread accessibility of platforms that enable individuals from various backgrounds to openly articulate their perspectives. The primary driver of this development can be attributed to the substantial expansion of mobile computing devices and the Internet. The extant academic literature suggests that the encounter with hate speech on online platforms has substantial consequences in real-life situations, especially for vulnerable communities. As a result, there has been consider

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Khwileh, Ahmad, Debasis Ganguly, and Gareth J. F. Jones. "Utilisation of Metadata Fields and Query Expansion in Cross-Lingual Search of User-Generated Internet Video." Journal of Artificial Intelligence Research 55 (January 27, 2016): 249–81. http://dx.doi.org/10.1613/jair.4775.

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Recent years have seen significant efforts in the area of Cross Language Information Retrieval (CLIR) for text retrieval. This work initially focused on formally published content, but more recently research has begun to concentrate on CLIR for informal social media content. However, despite the current expansion in online multimedia archives, there has been little work on CLIR for this content. While there has been some limited work on Cross-Language Video Retrieval (CLVR) for professional videos, such as documentaries or TV news broadcasts, there has to date, been no significant investigatio

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MUMOLO, ENZO, and MASSIMILIANO NOLICH. "TOWARDS ARTICULATORY CONTROL OF TALKING HEADS IN HUMANOID ROBOTICS USING A GENETIC-FUZZY IMITATION LEARNING ALGORITHM." International Journal of Humanoid Robotics 04, no. 01 (2007): 151–79. http://dx.doi.org/10.1142/s0219843607000959.

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In human heads there is a strong structural linkage between the vocal tract and facial behavior during speech. For a robotic talking head to have human-like behavior, this linkage should be emulated. One way to do that is to estimate the articulatory features from a given utterance and to use them to control a talking head. In this paper, we describe an algorithm to estimate the articulatory features from a spoken sentence using a novel computational model of human vocalization. Our model uses a set of fuzzy rules and genetic optimization. That is, the places of articulation are considered as

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Voievoda, K. V. "Innovative technologies based on artificial intelligence as a tool for modernization of the educational process in higher educational institutions." Scientific Notes of Junior Academy of Sciences of Ukraine, no. 1(32) (2025): 18–27. https://doi.org/10.51707/2618-0529-2025-32-03.

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In the context of global development of information and communication technologies and digitalization, the educational space is increasingly filled with innovative digital technologies, in particular based on artificial intelligence. The article explores ways to introduce innovative SMART-technologies into the educational process of higher education institutions. The increased interest of scientists in information and communication technologies is partly related to the development in 2022 of a digital product based on artificial intelligence ChatGPT and DALL. The neural network quickly gained

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Yu, Christina, Ralf W. Schlosser, Maurício Fontana de Vargas, Leigh Anne White, Rajinder Koul, and Howard C. Shane. "QuickPic AAC: An AI-Based Application to Enable Just-in-Time Generation of Topic-Specific Displays for Persons Who Are Minimally Speaking." International Journal of Environmental Research and Public Health 21, no. 9 (2024): 1150. http://dx.doi.org/10.3390/ijerph21091150.

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As artificial intelligence (AI) makes significant headway in various arenas, the field of speech–language pathology is at the precipice of experiencing a transformative shift towards automation. This study introduces QuickPic AAC, an AI-driven application designed to generate topic-specific displays from photographs in a “just-in-time” manner. Using QuickPic AAC, this study aimed to (a) determine which of two AI algorithms (NLG-AAC and GPT-3.5) results in greater specificity of vocabulary (i.e., percentage of vocabulary kept/deleted by clinician relative to vocabulary generated by QuickPic AAC

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SYSOYEV, P. V., and E. M. FILATOV. "COGNITIVE-MATRIX ANALYSIS AS A TOOL FOR EXPLORING CULTURAL IDENTITY OF A FICTION AUTHOR." Linguistics and Intercultural Communication 27, no. 2_2024 (2024): 38–54. http://dx.doi.org/10.55959/msu-2074-1588-19-27-2-3.

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The integration of artificial intelligence (AI) technologies into the educational system in general and foreign language teaching in particular makes it possible to significantly enhance students’ foreign language practice and create conditions for more effective formation of foreign language communicative competence components. At the same time, the gradual implementation of AI tools in the educational process, along with its obvious advantages, may cause teachers’ concerns related to the gradual exclusion of the teacher from the learning process and their complete replacement by AI. As a mod

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Rubab, Uzma. "The Role of Artificial Intelligence in Political Advertising and Crisis Communication: A Case Study of AI-Generated Speech of a Political Leader." Research Journal for Societal Issues 6, no. 3 (2024): 35–45. http://dx.doi.org/10.56976/rjsi.v6i3.258.

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Artificial Intelligence has become a basic necessity in 20th century with the emergence of new AI tools and APPs. As artificial intelligence has occupied the functionality of major human based activities, its integration is also seeing a transformative shift in political advertising, especially in the creation of speeches and in communicating party agendas to the general public and plying a vital role in opinion making and agenda setting. AI is already being used all over the globe to tailor the political speeches keeping in view the interests of specific voter segments. Recently the use of AI

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WANG, HSIAO-CHUAN, and HSIAO-FEN PAI. "RECOGNITION OF MANDARIN SYLLABLES BASED ON THE DISTRIBUTION OF TWO-DIMENSIONAL CEPSTRAL COEFFICIENTS." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 01 (1994): 247–57. http://dx.doi.org/10.1142/s0218001494000127.

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This paper presents a speech recognition method based on the distribution of two-dimensional cepstral (TDC) coefficients. For each recognition unit, a TDC matrix is calculated. A set of selected TDC coefficients forms a pattern to represent this speech segment. By assuming the Gaussian distribution of the TDC coefficients, a statistical model for a class of speech patterns is generated. The recognition process is to evaluate the probability of a TDC pattern belonging to a specific pattern class and to find the model which gives the highest probability. This method is applied to the recognition

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Vladyslava, Samoilenko. "AI and Deepface Influencers: The Challenge of Authenticity in the Online Space." Universal Library of Engineering Technology 02, no. 02 (2025): 21–26. https://doi.org/10.70315/uloap.ulete.2025.0202004.

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The article investigates the phenomenon of AI influencers generated with DeepFake technologies and examines their impact on the authenticity of digital content, audience trust, and the economic models of marketing. It outlines the technological foundations—generative adversarial networks (GANs), variational autoencoders (VAEs), diffusion models, transformers, text-to-speech systems, and voice conversion—and proposes a classification of AI influencers by modality (visual, audio, textual, and multimodal). The methodological framework rests on a comparative analysis of previous studies in the fie

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Esha Munir, Dr. Zahida Hussain, and Shama Fatima. "Man vs. Machine: A Comparative Study of AI and Human-Generated Narratives." Indus Journal of Social Sciences 3, no. 2 (2025): 367–76. https://doi.org/10.59075/ijss.v3i2.1235.

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The research aims to show that AI systems can create human like narratives that resonate and captivate the readers and how they are different from the human narratives. Artificial Intelligence (AI) is the imitation of cognitive ability in the devices that act or think like humans. It performs various tasks like reasoning, problem solving, learning, language understanding and perception based on human intelligence. As the world becomes more digitalized, AI will appear as the backbone of progressive education, making learning more accessible, adoptive, and cognitive. With developments like Meta

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Herasymova, O. I. "THE TRANSFORMATIVE IMPACT OF ARTIFICIAL INTELLIGENCE ON FOREIGN LANGUAGE TEACHING: CHALLENGES AND OPPORTUNITIES." INTELLIGENCE. PERSONALITY. CIVILIZATION, no. 2(29) (December 30, 2024): 5–12. https://doi.org/10.33274/2079-4835-2024-29-2-5-12.

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Objective. The objective of this article is to investigate the transformative impact of artificial intelligence on foreign language teaching, focusing on its applications, challenges, and opportunities in modern education. Methods. The primary scientific results are achieved through the use of a comprehensive set of general scientific and specialized research methods, including: analysis and synthesis of scientific literature on artificial intelligence and its applications in foreign language teaching; theoretical generalization and specification of AI integration in educational methodologies;

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Ostapenko, Svetlana. "Communicative Model of Messages in User-Dialogue Agent Interaction in Text Generation Systems." Scientific Research and Development. Modern Communication Studies 14, no. 2 (2025): 79–85. https://doi.org/10.12737/2587-9103-2025-14-2-79-85.

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The article focuses on the linguistic reception of the message content model in the "human – dialogue agent" communication system. The introduction of artificial intelligence (AI) tools changes the communication paradigm, creating new interactions between humans and AI agents while raising issues of perception and interpretation of generated texts. This study aims to analyze the functional components of the communicative message model during text generation. The author examines user interactions with Yandex and Google dialogue systems using linguistic modeling, formal analysis, and communicati

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RUSTEMI, Avni, Vladimir ATANASOVSKI, Valentina ANGELKOSKA, and Aleksandar RISTESKI. "IMPLEMENTATION AND PERFORMANCE ANALYSIS OF A PRACTICAL SYSTEM FOR DIPLOMA VERIFICATION BASED ON BLOCKCHAIN AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES." Journal of Natural Sciences and Mathematics of UT-JNSM 9, no. 17-18 (2024): 284–93. http://dx.doi.org/10.62792/ut.jnsm.v9.i17-18.p2823.

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The development of artificial intelligence in combination with blockchain features is marking a technological revolution in terms of the creation of different intelligent robots, and softbots, and more and more attempts are being made to create an artificial human who will be able to help, understand both the speech and the feelings of the real man. Regarding the implementation of decentralized artificial intelligence in institutions of higher education, there are delays in the implementation of blockchain systems for managing large and variable data. This is mainly due to some unique characte

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Voroshilova, Anastasiia Igorevna. "Artificial Intelligence in Sociological Research: Experience of Using It for Interview Processing and Analysis." Социодинамика, no. 2 (February 2025): 1–13. https://doi.org/10.25136/2409-7144.2025.2.73330.

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Currently, artificial intelligence is actively developing and being integrated into all aspects of human life, including science, resulting in both threats and opportunities that require careful consideration. Artificial intelligence can significantly influence the quality and effectiveness of sociological research. This article is dedicated to analyzing and describing the experience of using artificial intelligence, particularly the GPT-4o mini model, in sociological studies for processing and analyzing qualitative data obtained from semi-structured interviews. The author examines the possibi

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Kauser, SK Heena, I. Meghana, A. Mounika, B. Rajeswari, and Dr A. Seshagiri Rao. "Design and Implementation of Student Chat Bot using Machine Learning." International Journal of Innovative Research in Engineering & Management 9, no. 6 (2022): 60–64. http://dx.doi.org/10.55524/ijirem.2022.9.6.10.

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Students today are confronted with numerous issues regarding college student information.In a college, there is no effective communication channel for obtaining necessary student information.The automation of web-based communication using computer programming is the primary focus of this paper.A chat bot, or conversational agent that responds to user statements, is created using a computer program.It is able to receive user input in a variety of formats, including speech and text.The appropriate response to the user's query is generated by combining LSA (Latent Semantic Analysis) and AIML (Art

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GALIANO, I., E. SANCHIS, F. CASACUBERTA, and I. TORRES. "ACOUSTIC-PHONETIC DECODING OF SPANISH CONTINUOUS SPEECH." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 01 (1994): 155–80. http://dx.doi.org/10.1142/s0218001494000073.

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The design of current acoustic-phonetic decoders for a specific language involves the selection of an adequate set of sublexical units, and a choice of the mathematical framework for modelling the corresponding units. In this work, the baseline chosen for continuous Spanish speech consists of 23 sublexical units that roughly correspond to the 24 Spanish phonemes. The process of selection of such a baseline was based on language phonetic criteria and some experiments with an available speech corpora. On the other hand, two types of models were chosen for this work, conventional Hidden Markov Mo

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Llansó, Emma J. "No amount of “AI” in content moderation will solve filtering’s prior-restraint problem." Big Data & Society 7, no. 1 (2020): 205395172092068. http://dx.doi.org/10.1177/2053951720920686.

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Contemporary policy debates about managing the enormous volume of online content have taken a renewed focus on upload filtering, automated detection of potentially illegal content, and other “proactive measures”. Often, policymakers and tech industry players invoke artificial intelligence as the solution to complex challenges around online content, promising that AI is a scant few years away from resolving everything from hate speech to harassment to the spread of terrorist propaganda. Missing from these promises, however, is an acknowledgement that proactive identification and automated remov

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Vougioukas, Konstantinos, Stavros Petridis, and Maja Pantic. "Realistic Speech-Driven Facial Animation with GANs." International Journal of Computer Vision 128, no. 5 (2019): 1398–413. http://dx.doi.org/10.1007/s11263-019-01251-8.

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Abstract Speech-driven facial animation is the process that automatically synthesizes talking characters based on speech signals. The majority of work in this domain creates a mapping from audio features to visual features. This approach often requires post-processing using computer graphics techniques to produce realistic albeit subject dependent results. We present an end-to-end system that generates videos of a talking head, using only a still image of a person and an audio clip containing speech, without relying on handcrafted intermediate features. Our method generates videos which have (

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Abhinand, K. R., and H. K. Anasuya Devi. "An Approach for Generating Pattern-Based Shorthand Using Speech-to-Text Conversion and Machine Learning." Journal of Intelligent Systems 22, no. 3 (2013): 229–40. http://dx.doi.org/10.1515/jisys-2013-0039.

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AbstractRapid handwriting, popularly known as shorthand, involves writing symbols and abbreviations in lieu of common words or phrases. This method increases the speed of transcription and is primarily used to record oral dictation. Someone skilled in shorthand will be able to write as fast as the dictation occurs, and these patterns are later transliterated into actual, natural language words. A new kind of rapid handwriting scheme is proposed, called the Pattern-Based Shorthand. A word on a keyboard involves pressing a unique sequence of keys in a particular order. This sequence forms a patt

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Mankoo, Sandeep Singh. "DeepFakes- The Digital Threat in the Real World." Gyan Management Journal 17, no. 1 (2023): 71–77. http://dx.doi.org/10.48165/gmj.2022.17.1.8.

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Objectives: Understanding and Tackling the alarming surge of Digital Imposters known as the world of DeepFakes.  Methods: Using Artificial Intelligence based Deep Machine Learning software; Cyber Forensics; Physical mind awareness and alertness! Deepfakes use Artificial Intelligence and Deep Machine Learning techniques to make fake images, of people and events, which are as attractive/ authentic as the original. Deepfakes is the next big Challenge  in Cyber Security, taking the Security mindset to the next high level. Findings: On date we have no Specialized High-Tech support at ha

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Mrozek, Yevhen R. "Modern Approaches to Speech Recognition Tasks." Control Systems and Computers, no. 4 (308) (December 2024): 39–49. https://doi.org/10.15407/csc.2024.04.039.

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Introduction. The necessity for modern approaches to solving speech recognition tasks arises from the rapid development of artificial intelligence and the need to improve the accuracy and speed of human-computer interaction in various areas, such as voice assistants, translation, and automation. This direction is becoming increasingly relevant due to the growing volume of generated audio data and the need for real-time processing, particularly in Ukrainian contexts where multiple languages and dialects coexist. Currently, several approaches to speech recognition, analysis, and transcription ex

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Madhusudhana Rao, T. V., Suribabu Korada, and Y. Srinivas. "Machine hearing system for teleconference authentication with effective speech analysis." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 3 (2021): 357–65. http://dx.doi.org/10.3233/kes-210079.

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The speaker identification in Teleconferencing scenario, it is important to address whether a particular speaker is a part of a conference or not and to note that whether a particular speaker is spoken at the meeting or not. The feature vectors are extracted using MFCC-SDC-LPC. The Generalized Gamma Distribution is used to model the feature vectors. K-means algorithm is utilized to cluster the speech data. The test speaker is to be verified that he/she is a participant in the conference. A conference database is generated with 50 speakers. In order to test the model, 20 different speakers not

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