Sung-Jung Hsiao¹, Wen-Tsai Sung^2,*

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3817-3832, 2023, DOI:10.32604/cmc.2023.037380 - 31 March 2023

Abstract Speech plays an extremely important role in social activities. Many individuals suffer from a “speech barrier,” which limits their communication with others. In this study, an improved speech recognition method is proposed that addresses the needs of speech-impaired and deaf individuals. A basic improved connectionist temporal classification convolutional neural network (CTC-CNN) architecture acoustic model was constructed by combining a speech database with a deep neural network. Acoustic sensors were used to convert the collected voice signals into text or corresponding voice signals to improve communication. The method can be extended to modern artificial intelligence techniques, More >

Mohamad Khairi Ishak¹, Dag Øivind Madsen^2,*, Fahad Ahmed Al-Zahrani³

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1951-1961, 2023, DOI:10.32604/iasc.2023.033971 - 05 January 2023

Abstract Natural language processing technologies have become more widely available in recent years, making them more useful in everyday situations. Machine learning systems that employ accessible datasets and corporate work to serve the whole spectrum of problems addressed in computational linguistics have lately yielded a number of promising breakthroughs. These methods were particularly advantageous for regional languages, as they were provided with cutting-edge language processing tools as soon as the requisite corporate information was generated. The bulk of modern people are unconcerned about the importance of reading. Reading aloud, on the other hand, is an effective… More >

Mohammed Hadwan^1,2,*, Hamzah A. Alsayadi^3,4, Salah AL-Hagree⁵

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3471-3487, 2023, DOI:10.32604/cmc.2023.033457 - 31 October 2022

Abstract The attention-based encoder-decoder technique, known as the trans-former, is used to enhance the performance of end-to-end automatic speech recognition (ASR). This research focuses on applying ASR end-to-end transformer-based models for the Arabic language, as the researchers’ community pays little attention to it. The Muslims Holy Qur’an book is written using Arabic diacritized text. In this paper, an end-to-end transformer model to building a robust Qur’an vs. recognition is proposed. The acoustic model was built using the transformer-based model as deep learning by the PyTorch framework. A multi-head attention mechanism is utilized to represent the encoder and… More >

Sneha Basak¹, Himanshi Agrawal¹, Shreya Jena¹, Shilpa Gite^2,*, Mrinal Bachute², Biswajeet Pradhan^3,4,5,*, 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 >

Kuntharrgyal Khysru^1,*, Jianguo Wei^1,2, Jianwu Dang³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4897-4907, 2022, DOI:10.32604/cmc.2022.027591 - 28 July 2022

Abstract In China, Tibetan is usually divided into three major dialects: the Am-do, Khams and Lhasa dialects. The Am-do dialect evolved from ancient Tibetan and is a local variant of modern Tibetan. Although this dialect has its own specific historical and social conditions and development, there have been different degrees of communication with other ethnic groups, but all the abovementioned dialects developed from the same language: Tibetan. This paper uses the particularity of Tibetan suffixes in pronunciation and proposes a lexicon for the Am-do language, which optimizes the problems existing in previous research. Audio data of… More >

Sana Yasin¹, Umar Draz^2,3,*, Tariq Ali⁴, Kashaf Shahid¹, Amna Abid¹, Rukhsana Bibi¹, Muhammad Irfan⁵, Mohammed A. Huneif⁶, Sultan A. Almedhesh⁶, Seham M. Alqahtani⁶, Alqahtani Abdulwahab⁶, Mohammed Jamaan Alzahrani⁶, Dhafer Batti Alshehri⁶, Alshehri Ali Abdullah⁷, Saifur Rahman⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4349-4367, 2022, DOI:10.32604/cmc.2022.028251 - 16 June 2022

Abstract Diagnosing a baby’s feelings poses a challenge for both doctors and parents because babies cannot explain their feelings through expression or speech. Understanding the emotions of babies and their associated expressions during different sensations such as hunger, pain, etc., is a complicated task. In infancy, all communication and feelings are propagated through cry-speech, which is a natural phenomenon. Several clinical methods can be used to diagnose a baby’s diseases, but nonclinical methods of diagnosing a baby’s feelings are lacking. As such, in this study, we aimed to identify babies’ feelings and emotions through their cry… More >

Zhijie Wang¹, Yue Zhao^1,*, Licheng Wu¹, Xiaojun Bi¹, Zhuoma Dawa², Qiang Ji³

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 629-639, 2022, DOI:10.32604/cmc.2022.027092 - 18 May 2022

Abstract As one of Chinese minority languages, Tibetan speech recognition technology was not researched upon as extensively as Chinese and English were until recently. This, along with the relatively small Tibetan corpus, has resulted in an unsatisfying performance of Tibetan speech recognition based on an end-to-end model. This paper aims to achieve an accurate Tibetan speech recognition using a small amount of Tibetan training data. We demonstrate effective methods of Tibetan end-to-end speech recognition via cross-language transfer learning from three aspects: modeling unit selection, transfer learning method, and source language selection. Experimental results show that the More >

Kamal Jambi^1,*, Hassanin Al-Barhamtoshy¹, Wajdi Al-Jedaibi¹, Mohsen Rashwan², Sherif Abdou³

Computer Systems Science and Engineering, Vol.43, No.3, pp. 1155-1173, 2022, DOI:10.32604/csse.2022.024967 - 09 May 2022

Abstract Any natural language may have dozens of accents. Even though the equivalent phonemic formation of the word, if it is properly called in different accents, humans do have audio signals that are distinct from one another. Among the most common issues with speech, the processing is discrepancies in pronunciation, accent, and enunciation. This research study examines the issues of detecting, fixing, and summarising accent defects of average Arabic individuals in English-speaking speech. The article then discusses the key approaches and structure that will be utilized to address both accent flaws and pronunciation issues. The proposed… More >

Muhammad Babar Kamal¹, Arfat Ahmad Khan², Faizan Ahmed Khan³, Malik Muhammad Ali Shahid⁴, Chitapong Wechtaisong^2,*, Muhammad Daud Kamal⁵, Muhammad Junaid Ali⁶, Peerapong Uthansakul²

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5547-5562, 2022, DOI:10.32604/cmc.2022.024590 - 21 April 2022

Abstract The deep learning advancements have greatly improved the performance of speech recognition systems, and most recent systems are based on the Recurrent Neural Network (RNN). Overall, the RNN works fine with the small sequence data, but suffers from the gradient vanishing problem in case of large sequence. The transformer networks have neutralized this issue and have shown state-of-the-art results on sequential or speech-related data. Generally, in speech recognition, the input audio is converted into an image using Mel-spectrogram to illustrate frequencies and intensities. The image is classified by the machine learning mechanism to generate a… More >

Ravindra Parshuram Bachate¹, Ashok Sharma², Amar Singh³, Ayman A. Aly⁴, Abdulaziz H. Alghtani⁴, Dac-Nhuong Le^5,6,*

Computer Systems Science and Engineering, Vol.43, No.2, pp. 439-454, 2022, DOI:10.32604/csse.2022.024214 - 20 April 2022

Abstract Communication is a significant part of being human and living in the world. Diverse kinds of languages and their variations are there; thus, one person can speak any language and cannot effectively communicate with one who speaks that language in a different accent. Numerous application fields such as education, mobility, smart systems, security, and health care systems utilize the speech or voice recognition models abundantly. Though, various studies are focused on the Arabic or Asian and English languages by ignoring other significant languages like Marathi that leads to the broader research motivations in regional languages.… More >