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  • Open Access

    REVIEW

    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 - 27 October 2022

    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

    ARTICLE

    Two-Stage Low-Carbon Economic Dispatch of Integrated Demand Response-Enabled Integrated Energy System with Ladder-Type Carbon Trading

    Song Zhang1, Wensheng Li2, Zhao Li2, Xiaolei Zhang1, Zhipeng Lu1, Xiaoning Ge3,*

    Energy Engineering, Vol.120, No.1, pp. 181-199, 2023, DOI:10.32604/ee.2022.022228 - 27 October 2022

    Abstract Driven by the goal of “carbon neutrality” and “emission peak”, effectively controlling system carbon emissions has become significantly important to governments around the world. To this end, a novel two-stage low-carbon economic scheduling framework that considers the coordinated optimization of ladder-type carbon trading and integrated demand response (IDR) is proposed in this paper for the integrated energy system (IES), where the first stage determines the energy consumption plan of users by leveraging the price-based electrical-heat IDR. In contrast, the second stage minimizes the system total cost to optimize the outputs of generations with consideration of More >

  • Open Access

    ARTICLE

    The Application of Fertilizer and AMF Promotes Growth and Reduces the Cadmium and Lead Contents of Ryegrass (Lolium multiflorum L.) in a Copper Mining Area

    Jiaxin Chen1,#, Jiawei Guo1,#, Zhixin Yang1, Jiqing Yang2,*, Hengwen Dong3, Huiyun Wang3, Yalei Wang3, Fangdong Zhan1,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.2, pp. 471-485, 2023, DOI:10.32604/phyton.2022.023660 - 12 October 2022

    Abstract Heavy metal-polluted soil was collected from the Pulang copper mine in Shangri-La City, Yunnan Province, Southwest China. The effects of fertilizer (organic and inorganic) and arbuscular mycorrhizal fungi (AMF) on ryegrass (Lolium multiflorum L.) growth, root morphology, mineral nutrition and cadmium (Cd) and lead (Pb) contents were investigated by pot experiments. The results showed that both fertilizer and AMF significantly ameliorated the root morphology and mineral nutrition, reduced the Cd and Pb contents, and promoted the growth of ryegrass. Among all treatments, the combined application of organic–inorganic compound fertilizer with AMF had the highest effect, resulting… More >

  • Open Access

    ARTICLE

    Automatic Detection of Outliers in Multi-Channel EMG Signals Using MFCC and SVM

    Muhammad Irfan1, Khalil Ullah2, Fazal Muhammad3,*, Salman Khan3, Faisal Althobiani4, Muhammad Usman5, Mohammed Alshareef4, Shadi Alghaffari4, Saifur Rahman1

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 169-181, 2023, DOI:10.32604/iasc.2023.032337 - 29 September 2022

    Abstract The automatic detection of noisy channels in surface Electromyogram (sEMG) signals, at the time of recording, is very critical in making a noise-free EMG dataset. If an EMG signal contaminated by high-level noise is recorded, then it will be useless and can’t be used for any healthcare application. In this research work, a new machine learning-based paradigm is proposed to automate the detection of low-level and high-level noises occurring in different channels of high density and multi-channel sEMG signals. A modified version of mel frequency cepstral coefficients (mMFCC) is proposed for the extraction of features… More >

  • Open Access

    ARTICLE

    The Efficacy of Deep Learning-Based Mixed Model for Speech Emotion Recognition

    Mohammad Amaz Uddin1, Mohammad Salah Uddin Chowdury1, Mayeen Uddin Khandaker2,*, Nissren Tamam3, Abdelmoneim Sulieman4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1709-1722, 2023, DOI:10.32604/cmc.2023.031177 - 22 September 2022

    Abstract Human speech indirectly represents the mental state or emotion of others. The use of Artificial Intelligence (AI)-based techniques may bring revolution in this modern era by recognizing emotion from speech. In this study, we introduced a robust method for emotion recognition from human speech using a well-performed preprocessing technique together with the deep learning-based mixed model consisting of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN). About 2800 audio files were extracted from the Toronto emotional speech set (TESS) database for this study. A high pass and Savitzky Golay Filter have been used to More >

  • Open Access

    ARTICLE

    Influence of Dowel Center Spacing on Chamfered-Joint Components Made by Cupressus funebris Wood

    Jianhua Lyu1,2,#, Jialei Wang1,2,#, Ziqiang Chen3, Ming Chen1,2,*

    Journal of Renewable Materials, Vol.11, No.1, pp. 309-319, 2023, DOI:10.32604/jrm.2022.021478 - 10 August 2022

    Abstract The traditional tenon and mortise joint has low processing efficiency and a weak theoretical basis, making the structure easy to deform and damage, reducing the safety, and increasing waste of resources. This study aims to determine the optimum dowel center spacing parameter for chamfered-joint components and the maximum value of the strength of joints loaded into bending strength and tensile strength. In this study, an integrated optimization method combining the single-factor test and one-way ANOVA analysis was proposed to study the influence of the dowel center spacing on the bending strength and the tensile strength More >

  • Open Access

    ARTICLE

    Evaluating Partitioning Based Clustering Methods for Extended Non-negative Matrix Factorization (NMF)

    Neetika Bhandari1,*, Payal Pahwa2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2043-2055, 2023, DOI:10.32604/iasc.2023.028368 - 19 July 2022

    Abstract Data is humongous today because of the extensive use of World Wide Web, Social Media and Intelligent Systems. This data can be very important and useful if it is harnessed carefully and correctly. Useful information can be extracted from this massive data using the Data Mining process. The information extracted can be used to make vital decisions in various industries. Clustering is a very popular Data Mining method which divides the data points into different groups such that all similar data points form a part of the same group. Clustering methods are of various types. More >

  • Open Access

    ARTICLE

    Speech Separation Methodology for Hearing Aid

    Joseph Sathiadhas Esra1,*, Y. Sukhi2

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1659-1678, 2023, DOI:10.32604/csse.2023.025969 - 15 June 2022

    Abstract In the design of hearing aids (HA), the real-time speech-enhancement is done. The digital hearing aids should provide high signal-to-noise ratio, gain improvement and should eliminate feedback. In generic hearing aids the performance towards different frequencies varies and non uniform. Existing noise cancellation and speech separation methods drops the voice magnitude under the noise environment. The performance of the HA for frequency response is non uniform. Existing noise suppression methods reduce the required signal strength also. So, the performance of uniform sub band analysis is poor when hearing aid is concern. In this paper, a More >

  • Open Access

    ARTICLE

    Detection of Toxic Content on Social Networking Platforms Using Fine Tuned ULMFiT Model

    Hafsa Naveed1, Abid Sohail2, Jasni Mohamad Zain3,*, Noman Saleem4, Rao Faizan Ali5, Shahid Anwar6

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 15-30, 2023, DOI:10.32604/iasc.2023.023277 - 06 June 2022

    Abstract Question and answer websites such as Quora, Stack Overflow, Yahoo Answers and Answer Bag are used by professionals. Multiple users post questions on these websites to get the answers from domain specific professionals. These websites are multilingual meaning they are available in many different languages. Current problem for these types of websites is to handle meaningless and irrelevant content. In this paper we have worked on the Quora insincere questions (questions which are based on false assumptions or questions which are trying to make a statement rather than seeking for helpful answers) dataset in order More >

  • Open Access

    ARTICLE

    Arrhythmia Prediction on Optimal Features Obtained from the ECG as Images

    Fuad A. M. Al-Yarimi*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 129-142, 2023, DOI:10.32604/csse.2023.024297 - 01 June 2022

    Abstract A critical component of dealing with heart disease is real-time identification, which triggers rapid action. The main challenge of real-time identification is illustrated here by the rare occurrence of cardiac arrhythmias. Recent contributions to cardiac arrhythmia prediction using supervised learning approaches generally involve the use of demographic features (electronic health records), signal features (electrocardiogram features as signals), and temporal features. Since the signal of the electrical activity of the heartbeat is very sensitive to differences between high and low heartbeats, it is possible to detect some of the irregularities in the early stages of arrhythmia. More >

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