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Search Results (13)
  • Open Access


    A Novel Human Interaction Framework Using Quadratic Discriminant Analysis with HMM

    Tanvir Fatima Naik Bukht1, Naif Al Mudawi2, Saud S. Alotaibi3, Abdulwahab Alazeb2, Mohammed Alonazi4, Aisha Ahmed AlArfaj5, Ahmad Jalal1, Jaekwang Kim6,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1557-1573, 2023, DOI:10.32604/cmc.2023.041335

    Abstract Human-human interaction recognition is crucial in computer vision fields like surveillance, human-computer interaction, and social robotics. It enhances systems’ ability to interpret and respond to human behavior precisely. This research focuses on recognizing human interaction behaviors using a static image, which is challenging due to the complexity of diverse actions. The overall purpose of this study is to develop a robust and accurate system for human interaction recognition. This research presents a novel image-based human interaction recognition method using a Hidden Markov Model (HMM). The technique employs hue, saturation, and intensity (HSI) color transformation to… More >

  • Open Access


    Challenges and Limitations in Speech Recognition Technology: A Critical Review of Speech Signal Processing Algorithms, Tools and Systems

    Sneha Basak1, Himanshi Agrawal1, Shreya Jena1, Shilpa Gite2,*, Mrinal Bachute2, Biswajeet Pradhan3,4,5,*, Mazen Assiri4

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1053-1089, 2023, DOI:10.32604/cmes.2022.021755

    Abstract Speech recognition systems have become a unique human-computer interaction (HCI) family. Speech is one of the most naturally developed human abilities; speech signal processing opens up a transparent and hand-free computation experience. This paper aims to present a retrospective yet modern approach to the world of speech recognition systems. The development journey of ASR (Automatic Speech Recognition) has seen quite a few milestones and breakthrough technologies that have been highlighted in this paper. A step-by-step rundown of the fundamental stages in developing speech recognition systems has been presented, along with a brief discussion of various More >

  • Open Access


    Spectral Vacancy Prediction Using Time Series Forecasting for Cognitive Radio Applications

    Vineetha Mathai*, P. Indumathi

    Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1729-1746, 2022, DOI:10.32604/iasc.2022.024234

    Abstract An identification of unfilled primary user spectrum using a novel method is presented in this paper. Cooperation among users with the utilization of machine learning methods is analyzed. Learning methods are applied to construct the classifier, which selects the suitable fusion algorithm for the considered environment so that the out of band sensing is performed efficiently. Sensing performance is looked into with the existence of fading and it is observed that sensing performance degrades with fading which coincides with earlier findings. From the simulation, it can be inferred that Weibull fading outperforms all the other… More >

  • Open Access


    Hybrid GrabCut Hidden Markov Model for Segmentation

    Soobia Saeed1,*, Afnizanfaizal Abdullah1, N. Z. Jhanjhi2, Mehmood Naqvi3, Mehedi Masud4, Mohammed A. AlZain5

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 851-869, 2022, DOI:10.32604/cmc.2022.024085

    Abstract Diagnosing data or object detection in medical images is one of the important parts of image segmentation especially those data which is less effective to identify in MRI such as low-grade tumors or cerebral spinal fluid (CSF) leaks in the brain. The aim of the study is to address the problems associated with detecting the low-grade tumor and CSF in brain is difficult in magnetic resonance imaging (MRI) images and another problem also relates to efficiency and less execution time for segmentation of medical images. For tumor and CSF segmentation using trained light field database… More >

  • Open Access


    Speech Recognition-Based Automated Visual Acuity Testing with Adaptive Mel Filter Bank

    Shibli Nisar1, Muhammad Asghar Khan2,*, Fahad Algarni3, Abdul Wakeel1, M. Irfan Uddin4, Insaf Ullah2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2991-3004, 2022, DOI:10.32604/cmc.2022.020376

    Abstract One of the most commonly reported disabilities is vision loss, which can be diagnosed by an ophthalmologist in order to determine the visual system of a patient. This procedure, however, usually requires an appointment with an ophthalmologist, which is both time-consuming and expensive process. Other issues that can arise include a lack of appropriate equipment and trained practitioners, especially in rural areas. Centered on a cognitively motivated attribute extraction and speech recognition approach, this paper proposes a novel idea that immediately determines the eyesight deficiency. The proposed system uses an adaptive filter bank with weighted… More >

  • Open Access


    Tampering Detection Approach of Arabic-Text Based on Contents Interrelationship

    Fahd N. Al-Wesabi1, Abdelzahir Abdelmaboud2,*, Adnan A. Zain3, Mohammed M. Almazah4, Ammar Zahary5

    Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 483-498, 2021, DOI:10.32604/iasc.2021.014322

    Abstract Text information depends primarily on natural languages processing. Improving the security and usability of text information shared through the public internet has therefore been the most demanding problem facing researchers. In contact and knowledge sharing through the Internet, the authentication of content and the identification of digital content are becoming a key problem. Therefore, in this paper, a fragile approach of zero-watermarking based on natural language processing has been developed for authentication of content and prevention of misuse of Arabic texts distributed over the Internet. According to the proposed approach, watermark embedding, and identification was… More >

  • Open Access


    Implementation of Embedded Technology-Based English Speech Identification and Translation System

    Zheng Zeng

    Computer Systems Science and Engineering, Vol.35, No.5, pp. 377-383, 2020, DOI:10.32604/csse.2020.35.377

    Abstract Due to the increase in globalization, communication between different countries has become more and more frequent. Language barriers are the most important issues in communication. Machine translation is limited to texts, and cannot be an adequate substitute for oral communication. In this study, a speech recognition and translation system based on embedded technology was developed for the purpose of English speech recognition and translation. The system adopted the Hidden Markov Model (HMM) and Windows CE operating system. Experiments involving English speech recognition and EnglishChinese translation found that the accuracy of the system in identifying English More >

  • Open Access


    A Hybrid Intelligent Approach for Content Authentication and Tampering Detection of Arabic Text Transmitted via Internet

    Fahd N. Al-Wesabi1,2,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 195-211, 2021, DOI:10.32604/cmc.2020.012088

    Abstract In this paper, a hybrid intelligent text zero-watermarking approach has been proposed by integrating text zero-watermarking and hidden Markov model as natural language processing techniques for the content authentication and tampering detection of Arabic text contents. The proposed approach known as Second order of Alphanumeric Mechanism of Markov model and Zero-Watermarking Approach (SAMMZWA). Second level order of alphanumeric mechanism based on hidden Markov model is integrated with text zero-watermarking techniques to improve the overall performance and tampering detection accuracy of the proposed approach. The SAMMZWA approach embeds and detects the watermark logically without altering the More >

  • Open Access


    Intelligent Speech Communication Using Double Humanoid Robots

    Li-Hong Juang1,*, Yi-Hua Zhao2

    Intelligent Automation & Soft Computing, Vol.26, No.2, pp. 291-301, 2020, DOI:10.31209/2020.100000164

    Abstract Speech recognition is one of the most convenient forms of human beings engaging in the exchanging of information. In this research, we want to make robots understand human language and communicate with each other through the human language, and to realize man–machine interactive and humanoid– robot interactive. Therefore, this research mainly studies NAO robots’ speech recognition and humanoid communication between double -humanoid robots. This paper introduces the future direction and application prospect of speech recognition as well as its basic method and knowledge of speech recognition fields. This research also proposes the application of the… More >

  • Open Access


    Accurate Location Prediction of Social‐Users Using mHMM

    Ahsan Hussain, Bettahally N. Keshavamurthy, Ravi Prasad K. Jagannath

    Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 473-486, 2019, DOI:10.31209/2018.11007092

    Abstract Prediction space of distinct check-in locations in Location-Based Social Networks is a challenge. In this paper, a thorough analysis of Foursquare Check-ins is done. Based on previous check-in sequences, next location of social-users is accurately predicted using multinomial-Hidden Markov Model (mHMM) with Steady-State probabilities. This information benefits security-agencies in tracking suspects and restaurant-owners to predict their customers’ arrivals at different venues on given days. Higher accuracy and Steady-State venuepopularities obtained for location-prediction using the proposed method, outperform various other baseline methods. More >

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